Capturing images under varying lighting conditions

FIELD OF THE INVENTION

This invention relates to an image capture device that includes a two-dimensional image sensor with improved light sensitivity and processing for image data therefrom.

BACKGROUND OF THE INVENTION

An image capture device depends on an electronic image sensor to create an electronic representation of a visual image. Examples of such electronic image sensors include charge coupled device (CCD) image sensors and active pixel sensor (APS) devices (APS devices are often referred to as CMOS sensors because of the ability to fabricate them in a Complementary Metal Oxide Semiconductor process). Typically, these image sensors include a number of light sensitive pixels, often arranged in a regular pattern of rows and columns. For capturing color images, a pattern of filters is typically fabricated on the pattern of pixels, with different filter materials being used to make individual pixels sensitive to only a portion of the visible light spectrum. The color filters necessarily reduce the amount of light reaching each pixel, and thereby reduce the light sensitivity of each pixel. A need persists for improving the light sensitivity, or photographic speed, of electronic color image sensors to permit images to be captured at lower light levels or to allow images at higher light levels to be captured with shorter exposure times.

Image sensors are either linear or two-dimensional. Generally, these sensors have two different types of applications. The two-dimensional sensors are typically suitable for image capture devices such as digital cameras, cell phones and other applications. Linear sensors are often used for scanning documents. In either case, when color filters are employed the image sensors have reduced sensitivity.

Therefore, there is a need for improving the light sensitivity for electronic capture devices that employ a single sensor with a two-dimensional array of pixels. Furthermore, there is a need for the improved light sensitivity to benefit the capture of scene detail as well as the capture of scene colors.

SUMMARY OF THE INVENTION

Briefly summarized, according to one aspect of the present invention, the invention provides a method for capturing a scene image under varying lighting conditions, comprising:

a) providing an image sensor having panchromatic and color pixels;

b) a user selecting a scene mode and adjusting the image capture exposure as a function of lighting conditions and the selected scene mode; and

c) capturing a scene by the image sensor using the adjusted exposure.

Methods for capturing scene images in accordance with the present invention are particularly suitable for low level lighting conditions, where such low level lighting conditions are the result of low scene lighting, short exposure time, small aperture, or other restriction on light reaching the sensor. Such methods can be used effectively in a broad range of applications.

These and other aspects, objects, features and advantages of the present invention will be more clearly understood and appreciated from a review of the following detailed description of the preferred embodiments and appended claims, and by reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a digital capture device in accordance with the present invention;

FIG. 2 (prior art) is conventional Bayer color filter array pattern showing a minimal repeating unit and a non-minimal repeating unit;

FIG. 3 provides representative spectral quantum efficiency curves for red, green, and blue pixels, as well as a wider spectrum panchromatic quantum efficiency, all multiplied by the transmission characteristics of an infrared cut filter;

FIGS. 4A-D provides minimal repeating units for several variations of a color filter array pattern of the present invention that has color pixels with the same color photoresponse arranged in rows or columns;

FIG. 5 shows the cell structure of the minimal repeating unit from FIG. 4A;

FIG. 6A is the interpolated panchromatic image for FIG. 4A;

FIG. 6B is the low-resolution color image corresponding to the cells in FIG. 4A and FIG. 5;

FIGS. 7A-C shows several ways of combining the pixels of FIG. 4A;

FIGS. 8A-D shows the color filter array pattern of FIG. 4A with color pixels that have alternative color photoresponse characteristics, including four color alternatives as well as a cyan, magenta, and yellow alternatives;

FIG. 9 provides a minimal repeating unit for an alternative color filter array of the present invention in which the panchromatic pixels are arranged in diagonal lines;

FIGS. 10A-B provides minimal repeating units for two variations of an alternative color filter array of the present invention in which the panchromatic pixels form a grid into which the color pixels are embedded;

FIGS. 11A-D provides minimal repeating units and tiling arrangements for two variations of an alternative color filter array of the present invention in which there are two colors per cell;

FIGS. 12A-B provides minimal repeating units for two variations of an alternative color filter array of the present invention in which there are two colors per cell and the panchromatic pixels are arranged in diagonal lines;

FIGS. 13A-C provides variations of FIG. 4A in which the minimal repeating unit is smaller than eight by eight pixels;

FIGS. 14A-B provides minimal repeating units for two variations of an alternative color filter array of the present invention in which the minimal repeating unit is six by six pixels;

FIGS. 15A-B provides minimal repeating units for two variations of an alternative color filter array of the present invention in which the minimal repeating unit is four by four pixels;

FIG. 16 is the minimal repeating unit of FIG. 4A with subscripts for individual pixels within the minimal repeating unit;

FIGS. 17A-E shows the panchromatic pixels and the color pixels of one cell of FIG. 16, and various ways in which the color pixels are combined;

FIG. 18 is a process diagram of the present invention showing the method of processing the color and panchromatic pixel data from a sensor of the present invention; and

FIGS. 19A-D illustrates methods of the present invention for interpolating missing colors in the low-resolution partial color image of FIG. 18.

DETAILED DESCRIPTION OF THE INVENTION

Because digital cameras employing imaging devices and related circuitry for signal capture and correction and for exposure control are well known, the present description will be directed in particular to elements forming part of, or cooperating more directly with, method and apparatus in accordance with the present invention. Elements not specifically shown or described herein are selected from those known in the art. Certain aspects of the embodiments to be described are provided in software. Given the system as shown and described according to the invention in the following materials, software not specifically shown, described or suggested herein that is useful for implementation of the invention is conventional and within the ordinary skill in such arts.

Turning now to FIG. 1, a block diagram of an image capture device shown as a digital camera embodying the present invention is shown. Although a digital camera will now be explained, the present invention is clearly applicable to other types of image capture devices. In the disclosed camera, light 10 from the subject scene is input to an imaging stage 11, where the light is focused by lens 12 to form an image on solid state image sensor 20. Image sensor 20 converts the incident light to an electrical signal for each picture element (pixel). The image sensor 20 of the preferred embodiment is a charge coupled device (CCD) type or an active pixel sensor (APS) type (APS devices are often referred to as CMOS sensors because of the ability to fabricate them in a Complementary Metal Oxide Semiconductor process). Other types of image sensors having two-dimensional array of pixels are used, provided that they employ the patterns of the present invention. The present invention also makes use of an image sensor 20 having a two-dimensional array of color and panchromatic pixels as will become clear later in this specification after FIG. 1 is described. Examples of the patterns of color and panchromatic pixels of the present invention that are used with the image sensor 20 are seen in FIGS. 4A-D, FIGS. 8A-D, FIG. 9, FIGS. 10A-B, FIG. 11A, FIG. 11C, FIGS. 13A-C, FIGS. 14A-B, and FIGS. 15A-B, although other patterns are used within the spirit of the present invention.

The image sensor 20 receives light 10 from a subject scene. The resulting electrical signal from each pixel of the image sensor 20 is typically related to both the intensity of the light reaching the pixel and the length of time the pixel is allowed to accumulate or integrate the signal from incoming light. This time is called the integration time or exposure time. In this context, the integration time is the time during which the shutter 18 allows light to reach the image sensor 20 and the image sensor is simultaneously operating to record the light. The combination of overall light intensity and integration time is called exposure. It is to be understood that equivalent exposures can be achieved by various combinations of light intensity and integration time. For example, a long integration time can be used with a scene of very low light intensity in order to achieve the same exposure as using a short integration time with a scene of high light intensity.

FIG. 1 includes several elements to regulate the exposure. The filter assembly 13 and the iris 14, modify the light intensity at the sensor. The shutter 18 provides a mechanism for allowing or preventing light from reaching the image sensor, while the timing generator 26 provides a way to control when the image sensor is actively recording the image. In this way, the shutter 18 and the timing generator 26 jointly determine the integration time. Iris block 14 controls the intensity of light reaching the image sensor 20 by using a mechanical aperture to block light in the optical path. The iris 14 can include a mechanical aperture with variable size, or it can include several fixed apertures of different size that can selectively be inserted into the optical path. Filter assembly block 13 provides another way to control the intensity of light reaching the image sensor 20 by selectively placing a light absorptive or light reflective filter in the optical path. This filter can be a neutral density filter that reduces all colors of light equally, or it can be a color balance filter that preferentially reduces some colors of light more than other colors. A color balance filter can be used, for example, when the scene is illuminated by incandescent light that provides relatively more red light than blue light. The filter assembly block 13 can include several filters that can selectively be inserted into the optical path either singly or in combinations. The shutter 18, also referred to as a mechanical shutter, typically includes a curtain or moveable blade connected to an actuator that removes the curtain or blade from the optical path at the start of integration time and inserts the curtain or blade into the optical path at the end of integration time. Some types of image sensors allow the integration time to be controlled electronically by resetting the image sensor and then reading out the image sensor some time later. The interval of time between reset and readout bounds the integration time and it is controlled by the timing generator block 26.

Although FIG. 1 shows several exposure controlling elements, some embodiments may not include one or more of these elements, or there may be alternative mechanisms of controlling exposure. These variations are to be expected in the wide range of image capture devices to which the present invention can be applied.

As previously mentioned, equivalent exposures can be achieved by various combinations of light intensity and integration time. Although the exposures are equivalent, a particular exposure combination of light intensity and integration time may be preferred over other equivalent exposures for capturing a given scene image. For example, a short integration time is generally preferred when capturing sporting events in order to avoid blurred images due to motion of athletes running or jumping during the integration time. In this case, the iris block can provide a large aperture for high light intensity and the shutter can provide a short integration time. This case serves as an example of a scene mode, specifically a sports scene mode that favors short integration times over small apertures. In general, scene modes are preferences for selecting and controlling the elements that combine to make an exposure in order optimally to capture certain scene types. Another example of a scene mode is a landscape scene mode. In this scene mode, preference is given to a small aperture to provide good depth of focus with the integration time being adjusted to provide optimum exposure. Yet another example of a scene mode is a general scene mode that favors small apertures for good depth of focus with integration time increasing with lower scene light levels, until the integration time becomes long enough for certain light levels that handheld camera shake becomes a concern, at which point the integration time remains fixed and the iris provides larger apertures to increase the light intensity at the sensor.

The exposure controller block 40 in FIG. 1 controls or adjusts the exposure regulating elements outlined above. The brightness sensor block 16 contains at least one sensor responsive to light in the visible spectrum. For example, brightness sensor block 16 can have a single sensor with a broad photoresponse, or it can have multiple sensors with narrow and differing photoresponses such as red, green, and blue. The brightness sensor block 16 provides at least one signal representing scene light intensity to the exposure controller block 40. If, for example, the brightness signal(s) received by exposure controller 40 indicate that the overall scene brightness level is too high for sensor 20, then exposure controller 40 can instruct the filter assembly block 13 to insert a particular ND filter into the optical path. Or, if a red brightness signal exceeds a blue brightness signal level by a specified amount, the exposure controller block 40 can instruct the filter assembly block 13 to insert a particular color balance filter into the optical path to compensate for the greater amount of red light being available. In addition to using filters from the filter assembly 13, the exposure controller 40 can instruct the iris 14 to open or close by various specified amounts, it can open or close the mechanical shutter 18, and it can indirectly control the timing generator 26 through the system controller 50. The exposure controller 40 can use any of these previously mentioned exposure control actions individually or in any combination.

The exposure controller 40 block also receives inputs from the user inputs block 74 and from the system controller block 50. Scene mode as described above is generally provided by the user as a user input. When taking multiple image captures in quick succession, scene lighting intensity for the next capture can also be estimated from the digitized image data taken on the previous capture. This image data, passing through the digital signal processor 36 and the system controller 50, can be used by the exposure controller 40 to augment or override digital signals from the brightness sensor 16.

The exposure controller block 40 uses the light intensity signal(s) from brightness sensor 16, user inputs 74 (including scene mode), and system controller 50 inputs to determine how to control the exposure regulating elements to provide an appropriate exposure. The exposure controller 40 can determine automatically how to control or adjust all the exposure regulating elements to produce a correct exposure. Alternatively, by way of the user inputs block 74, the user can manually control or adjust the exposure regulating elements to produce a user selected exposure. Furthermore, the user can manually control or adjust only some exposure regulating elements while allowing the exposure controller 40 to control the remaining elements automatically. The exposure controller also provides information regarding the exposure to the user through the viewfinder display 70 and the exposure display 72. This information for the user includes the automatically or manually determined integration time, aperture, and other exposure regulating elements. This information can also include to what degree an image capture will be underexposed or overexposed in case the correct exposure cannot be achieved based on the limits of operation of the various exposure regulating elements.

The image capture device, shown in FIG. 1 as a digital camera, can also include other features, for example, an autofocus system, or detachable and interchangeable lenses. It will be understood that the present invention is applied to any type of digital camera, or other image capture device, where similar functionality is provided by alternative components. For example, the digital camera is a relatively simple point and shoot digital camera, where the shutter 18 is a relatively simple movable blade shutter, or the like, instead of the more complicated focal plane arrangement. The present invention can also be practiced on imaging components included in non-camera devices such as mobile phones and automotive vehicles.

The analog signal from image sensor 20 is processed by analog signal processor 22 and applied to analog to digital (A/D) converter 24. Timing generator 26 produces various clocking signals to select rows and pixels and synchronizes the operation of analog signal processor 22 and A/D converter 24. The image sensor stage 28 includes the image sensor 20, the analog signal processor 22, the A/D converter 24, and the timing generator 26. The components of image sensor stage 28 are separately fabricated integrated circuits, or they are fabricated as a single integrated circuit as is commonly done with CMOS image sensors. The resulting stream of digital pixel values from A/D converter 24 is stored in memory 32 associated with digital signal processor (DSP) 36.

Digital signal processor 36 is one of three processors or controllers in this embodiment, in addition to system controller 50 and exposure controller 40. Although this partitioning of camera functional control among multiple controllers and processors is typical, these controllers or processors are combined in various ways without affecting the functional operation of the camera and the application of the present invention. These controllers or processors can comprise one or more digital signal processor devices, microcontrollers, programmable logic devices, or other digital logic circuits. Although a combination of such controllers or processors has been described, it should be apparent that one controller or processor is designated to perform all of the needed functions. All of these variations can perform the same function and fall within the scope of this invention, and the term “processing stage” will be used as needed to encompass all of this functionality within one phrase, for example, as in processing stage 38 in FIG. 1.

In the illustrated embodiment, DSP 36 manipulates the digital image data in its memory 32 according to a software program permanently stored in program memory 54 and copied to memory 32 for execution during image capture. DSP 36 executes the software necessary for practicing image processing shown in FIG. 18. Memory 32 includes of any type of random access memory, such as SDRAM. A bus 30 comprising a pathway for address and data signals connects DSP 36 to its related memory 32, A/D converter 24 and other related devices.

System controller 50 controls the overall operation of the camera based on a software program stored in program memory 54, which can include Flash EEPROM or other nonvolatile memory. This memory can also be used to store image sensor calibration data, user setting selections and other data which must be preserved when the camera is turned off. System controller 50 controls the sequence of image capture by directing exposure controller 40 to operate the lens 12, filter assembly 13, iris 14, and shutter 18 as previously described, directing the timing generator 26 to operate the image sensor 20 and associated elements, and directing DSP 36 to process the captured image data. After an image is captured and processed, the final image file stored in memory 32 is transferred to a host computer via interface 57, stored on a removable memory card 64 or other storage device, and displayed for the user on image display 88.

A bus 52 includes a pathway for address, data and control signals, and connects system controller 50 to DSP 36, program memory 54, system memory 56, host interface 57, memory card interface 60 and other related devices. Host interface 57 provides a high speed connection to a personal computer (PC) or other host computer for transfer of image data for display, storage, manipulation or printing. This interface is an IEEE1394 or USB2.0 serial interface or any other suitable digital interface. Memory card 64 is typically a Compact Flash (CF) card inserted into socket 62 and connected to the system controller 50 via memory card interface 60. Other types of storage that are utilized include without limitation PC-Cards, MultiMedia Cards (MMC), or Secure Digital (SD) cards.

Processed images are copied to a display buffer in system memory 56 and continuously read out via video encoder 80 to produce a video signal. This signal is output directly from the camera for display on an external monitor, or processed by display controller 82 and presented on image display 88. This display is typically an active matrix color liquid crystal display (LCD), although other types of displays are used as well.

The user interface, including all or any combination of viewfinder display 70, exposure display 72, status display 76 and image display 88, and user inputs 74, is controlled by a combination of software programs executed on exposure controller 40 and system controller 50. The Viewfinder Display, Exposure Display and the User Inputs displays are a user control and status interface 68. User inputs 74 typically include some combination of buttons, rocker switches, joysticks, rotary dials or touchscreens. Exposure controller 40 operates light metering, scene mode, autofocus, and other exposure functions. The system controller 50 manages the graphical user interface (GUI) presented on one or more of the displays, e.g., on image display 88. The GUI typically includes menus for making various option selections and review modes for examining captured images.

The ISO speed rating is an important attribute of a digital still camera. The exposure time, the lens aperture, the lens transmittance, the level and spectral distribution of the scene illumination, and the scene reflectance determine the exposure level of a digital still camera. When an image from a digital still camera is obtained using an insufficient exposure, proper tone reproduction can generally be maintained by increasing the electronic or digital gain, but the image will contain an unacceptable amount of noise. As the exposure is increased, the gain is decreased, and therefore the image noise can normally be reduced to an acceptable level. If the exposure is increased excessively, the resulting signal in bright areas of the image can exceed the maximum signal level capacity of the image sensor or camera signal processing. This can cause image highlights to be clipped to form a uniformly bright area, or to bloom into surrounding areas of the image. It is important to guide the user in setting proper exposures. An ISO speed rating is intended to serve as such a guide. In order to be easily understood by photographers, the ISO speed rating for a digital still camera should directly relate to the ISO speed rating for photographic film cameras. For example, if a digital still camera has an ISO speed rating of ISO 200, then the same exposure time and aperture should be appropriate for an ISO 200 rated film/process system.

The ISO speed ratings are intended to harmonize with film ISO speed ratings. However, there are differences between electronic and film-based imaging systems that preclude exact equivalency. Digital still cameras can include variable gain, and can provide digital processing after the image data has been captured, enabling tone reproduction to be achieved over a range of camera exposures. It is therefore possible for digital still cameras to have a range of speed ratings. This range is defined as the ISO speed latitude. To prevent confusion, a single value is designated as the inherent ISO speed rating, with the ISO speed latitude upper and lower limits indicating the speed range, that is, a range including effective speed ratings that differ from the inherent ISO speed rating. With this in mind, the inherent ISO speed is a numerical value calculated from the exposure provided at the focal plane of a digital still camera to produce specified camera output signal characteristics. The inherent speed is usually the exposure index value that produces peak image quality for a given camera system for normal scenes, where the exposure index is a numerical value that is inversely proportional to the exposure provided to the image sensor.

The digital camera as described can be configured and operated to capture a single image or to capture a stream of images. For example, the image sensor stage 28 can be configured to capture single full resolution images and the mechanical shutter 18 can be used to control the integration time. This case is well suited to single image capture for still photography. Alternatively, the image sensor stage can be configured to capture a stream of limited resolution images and the image sensor can be configured to control the integration time electronically. In this case a continuous stream of images may be captured without being limited by the readout speed of the sensor or the actuation speed of the mechanical shutter. This case is useful, for example, for capturing a stream of images that will be used to provide a video signal, as in the case of a video camera. The configurations outlined in these cases are examples of the configurations employed for single capture and capturing a stream of images, but alternative configurations can be used for single image capture and capturing a stream of images. The present invention can be practiced in image capture devices providing either for single image capture or for capturing a stream of images. Furthermore, image capture devices incorporating the present invention can allow the user to select between single image capture and capturing a stream of images.

The image sensor 20 shown in FIG. 1 typically includes a two-dimensional array of light sensitive pixels fabricated on a silicon substrate that provide a way of converting incoming light at each pixel into an electrical signal that is measured. As the sensor is exposed to light, free electrons are generated and captured within the electronic structure at each pixel. Capturing these free electrons for some period of time and then measuring the number of electrons captured, or measuring the rate at which free electrons are generated can measure the light level at each pixel. In the former case, accumulated charge is shifted out of the array of pixels to a charge to voltage measurement circuit as in a charge coupled device (CCD), or the area close to each pixel can contain elements of a charge to voltage measurement circuit as in an active pixel sensor (APS or CMOS sensor).

Whenever general reference is made to an image sensor in the following description, it is understood to be representative of the image sensor 20 from FIG. 1. It is further understood that all examples and their equivalents of image sensor architectures and pixel patterns of the present invention disclosed in this specification is used for image sensor 20.

In the context of an image sensor, a pixel (a contraction of “picture element”) refers to a discrete light sensing area and charge shifting or charge measurement circuitry associated with the light sensing area. In the context of a digital color image, the term pixel commonly refers to a particular location in the image having associated color values.

In order to produce a color image, the array of pixels in an image sensor typically has a pattern of color filters placed over them. FIG. 2 shows a pattern of red, green, and blue color filters that is commonly used. This particular pattern is commonly known as a Bayer color filter array (CFA) after its inventor Bryce Bayer as disclosed in U.S. Pat. No. 3,971,065. This pattern is effectively used in image sensors having a two-dimensional array of color pixels. As a result, each pixel has a particular color photoresponse that, in this case, is a predominant sensitivity to red, green or blue light. Another useful variety of color photoresponses is a predominant sensitivity to magenta, yellow, or cyan light. In each case, the particular color photoresponse has high sensitivity to certain portions of the visible spectrum, while simultaneously having low sensitivity to other portions of the visible spectrum. The term color pixel will refer to a pixel having a color photoresponse.

The set of color photoresponses selected for use in a sensor usually has three colors, as shown in the Bayer CFA, but it can also include four or more. As used herein, a panchromatic photoresponse refers to a photoresponse having a wider spectral sensitivity than those spectral sensitivities represented in the selected set of color photoresponses. A panchromatic photosensitivity can have high sensitivity across the entire visible spectrum. The term panchromatic pixel will refer to a pixel having a panchromatic photoresponse. Although the panchromatic pixels generally have a wider spectral sensitivity than the set of color photoresponses, each panchromatic pixel can have an associated filter. Such filter is either a neutral density filter or a color filter.

When a pattern of color and panchromatic pixels is on the face of an image sensor, each such pattern has a repeating unit that is a contiguous subarray of pixels that acts as a basic building block. By juxtaposing multiple copies of the repeating unit, the entire sensor pattern is produced. The juxtaposition of the multiple copies of repeating units are done in diagonal directions as well as in the horizontal and vertical directions.

A minimal repeating unit is a repeating unit such that no other repeating unit has fewer pixels. For example, the CFA in FIG. 2 includes a minimal repeating unit that is two pixels by two pixels as shown by pixel block 100 in FIG. 2. Multiple copies of this minimal repeating unit is tiled to cover the entire array of pixels in an image sensor. The minimal repeating unit is shown with a green pixel in the upper right corner, but three alternative minimal repeating units can easily be discerned by moving the heavy outlined area one pixel to the right, one pixel down, or one pixel diagonally to the right and down. Although pixel block 102 is a repeating unit, it is not a minimal repeating unit because pixel block 100 is a repeating unit and block 100 has fewer pixels than block 102.

An image captured using an image sensor having a two-dimensional array with the CFA of FIG. 2 has only one color value at each pixel. In order to produce a full color image, there are a number of techniques for inferring or interpolating the missing colors at each pixel. These CFA interpolation techniques are well known in the art and reference is made to the following patents: U.S. Pat. No. 5,506,619, U.S. Pat. No. 5,629,734, and U.S. Pat. No. 5,652,621.

FIG. 3 shows the relative spectral sensitivities of the pixels with red, green, and blue color filters in a typical camera application. The X-axis in FIG. 3 represents light wavelength in nanometers, and the Y-axis represents efficiency. In FIG. 3, curve 110 represents the spectral transmission characteristic of a typical filter used to block infrared and ultraviolet light from reaching the image sensor. Such a filter is needed because the color filters used for image sensors typically do not block infrared light, hence the pixels are unable to distinguish between infrared light and light that is within the passbands of their associated color filters. The infrared blocking characteristic shown by curve 110 prevents infrared light from corrupting the visible light signal. The spectralquantum efficiency, i.e. the proportion of incident photons that are captured and converted into a measurable electrical signal, for a typical silicon sensor with red, green, and blue filters applied is multiplied by the spectral transmission characteristic of the infrared blocking filter represented by curve 110 to produce the combined system quantum efficiencies represented by curve 114 for red, curve 116 for green, and curve 118 for blue. It is understood from these curves that each color photoresponse is sensitive to only a portion of the visible spectrum. By contrast, the photoresponse of the same silicon sensor that does not have color filters applied (but including the infrared blocking filter characteristic) is shown by curve 112; this is an example of a panchromatic photoresponse. By comparing the color photoresponse curves 114, 116, and 118 to the panchromatic photoresponse curve 112, it is clear that the panchromatic photoresponse is three to four times more sensitive to wide spectrum light than any of the color photoresponses.

The greater panchromatic sensitivity shown in FIG. 3 permits improving the overall sensitivity of an image sensor by intermixing pixels that include color filters with pixels that do not include color filters. However, the color filter pixels will be significantly less sensitive than the panchromatic pixels. In this situation, if the panchromatic pixels are properly exposed to light such that the range of light intensities from a scene cover the full measurement range of the panchromatic pixels, then the color pixels will be significantly underexposed. Hence, it is advantageous to adjust the sensitivity of the color filter pixels so that they have roughly the same sensitivity as the panchromatic pixels. The sensitivity of the color pixels are increased, for example, by increasing the size of the color pixels relative to the panchromatic pixels, with an associated reduction in spatial pixels.

FIG. 4A represents a two-dimensional array of pixels having two groups. Pixels from the first group of pixels have a narrower spectral photoresponse than pixels from the second group of pixels. The first group of pixels includes individual pixels that relate to at least two different spectral photoresponses corresponding to at least two color filters. These two groups of pixels are intermixed to improve the overall sensitivity of the sensor. As will become clearer in this specification, the placement of the first and second groups of pixels defines a pattern that has a minimal repeating unit including at least twelve pixels. The minimal repeating unit includes first and second groups of pixels arranged to permit the reproduction of a captured color image under different lighting conditions.

The complete pattern shown in FIG. 4A represents a minimal repeating unit that is tiled to cover an entire array of pixels. As with FIG. 2, there are several other minimal repeating units that are used to describe this overall arrangement of color and panchromatic pixels, but they are all essentially equivalent in their characteristics and each is a subarray of pixels, the subarray being eight pixels by eight pixels in extent. An important feature of this pattern is alternating rows of panchromatic and color pixels with the color rows having pixels with the same color photoresponse grouped together. The groups of pixels with the same photoresponse along with some of their neighboring panchromatic pixels are considered to form four cells that make up the minimal repeating unit, a cell being a contiguous subarray of pixels having fewer pixels than a minimal repeating unit.

These four cells, delineated by heavy lines in FIG. 4A and shown as cells 120, 122, 124, and 126 in FIG. 5, enclose four groups of four-by-four pixels each, with 120 representing the upper left cell, 122 representing the upper right cell, 124 representing the lower left cell, and 126 representing the lower right cell. Each of the four cells includes eight panchromatic pixels and eight color pixels of the same color photoresponse. The color pixels in a cell is combined to represent the color for that entire cell. Hence, cell 120 in FIG. 5 is considered to be a green cell, cell 122 is considered to be a red cell, and so on. Each cell includes at least two pixels of the same color, thereby allowing pixels of the same color to be combined to overcome the difference in photosensitivity between the color pixels and the panchromatic pixels.

In the case of a minimal repeating unit with four non-overlapping cells, with each cell having two pixels of the same color and two panchromatic pixels, it is clear that the minimal repeating unit includes sixteen pixels. In the case of a minimal repeating unit with three non-overlapping cells, with each cell having two pixels of the same color and two panchromatic pixels, it is clear that the minimal repeating unit includes twelve pixels.

In accordance with the present invention, the minimal repeating unit of FIG. 4A, when considered in light of the cell structure identified in FIG. 5, can represent the combination of a high-resolution panchromatic image and a low-resolution Bayer pattern color image arranged to permit the reproduction of a captured color image under different lighting conditions. The individual elements of the Bayer pattern image represent the combination of the color pixels in the corresponding cells. The first group of pixels defines a low-resolution color filter array image and the second group of pixels defines a high-resolution panchromatic image. See FIG. 6A and FIG. 6B. FIG. 6A represents the high-resolution panchromatic image corresponding to FIG. 4A, including both the panchromatic pixels P from FIG. 4A as well as interpolated panchromatic pixels P′; and FIG. 6B represents the low-resolution Bayer pattern color image, with R′, G′, and B′ representing for each of the cells outlined in FIG. 5 the cell color associated with the combined color pixels in the cell.

In the following discussion, all cells in FIGS. 4B-D, 8A-D, 9, 10A-B, 11A, 11C, 12A-B, 13A-C, 14A-B, and 15A-B are delineated by heavy lines, as they were in FIG. 4A.

In addition to alternative minimal repeating units of FIG. 4A, each cell of the pattern is rotated 90 degrees to produce the pattern shown in FIG. 4B. This is substantially the same pattern, but it places the highest panchromatic sampling frequency in the vertical direction instead of the horizontal direction. The choice to use FIG. 4A or FIG. 4B depends on whether or not it is desired to have higher panchromatic spatial sampling in either the horizontal or vertical directions respectively. However, it is clear that the resulting cells that make up the minimal repeating unit in both patterns produce the same low-resolution color image for both patterns. Hence, FIG. 4A and FIG. 4B are equivalent from a color perspective. In general, FIG. 4A and FIG. 4B are examples of practicing the present invention with the panchromatic pixels arranged linearly in either rows or columns. Furthermore, FIG. 4A has single rows of panchromatic pixels with each row separated from a neighboring row of panchromatic pixels by a row of color pixels; FIG. 4B has the same characteristic in the column direction.

FIG. 4C represents yet another alternative minimal repeating unit to FIG. 4A with essentially the same cell color characteristics. However, FIG. 4C shows the panchromatic and color rows staggered on a cell-by-cell basis. This can improve the vertical panchromatic resolution. Yet another alternative minimal repeating unit to FIG. 4A is represented in FIG. 4D, wherein the panchromatic and color rows are staggered by column pairs. This also has the potential of improving the vertical panchromatic resolution. A characteristic of all of the minimal repeating units of FIGS. 4A-D is that groups of two or more same color pixels are arranged side by side in either rows or columns.

FIGS. 4A-D all have the same color structure with the cells that constitute the minimal repeating unit expressing a low-resolution Bayer pattern. It can therefore be seen that a variety of arrangements of panchromatic pixels and grouped color pixels are constructed within the spirit of the present invention.

In order to increase the color photosensitivity to overcome the disparity between the panchromatic photosensitivity and the color photosensitivity, the color pixels within each cell is combined in various ways. For example, the charge from same colored pixels are combined or binned in a CCD image sensor or in types of active pixel sensors that permit binning. Alternatively, the voltages corresponding to the measured amounts of charge in same colored pixels are averaged, for example by connecting in parallel capacitors that are charged to these voltages. In yet another approach, the digital representations of the light levels at same colored pixels are summed or averaged. Combining or binning charge from two pixels doubles the signal level, while the noise associated with sampling and reading out the combined signal remains the same, thereby increasing the signal to noise ratio by a factor of two, representing a corresponding two times increase in the photosensitivity of the combined pixels. In the case of summing the digital representations of the light levels from two pixels, the resulting signal increases by a factor of two, but the corresponding noise levels from reading the two pixels combine in quadrature, thereby increasing the noise by the square root of two; the resulting signal to noise ratio of the combined pixels therefore increases by the square root of two over the uncombined signals. A similar analysis applies to voltage or digital averaging.

The previously mentioned approaches for combining signals from same colored pixels within a cell is used singly or in combinations. For example, by vertically combining the charge from same colored pixels in FIG. 4A in groups of two to produce the combined pixels with combined signals R′, G′, and B′ shown in FIG. 7A. In this case, each R′, G′, and B′ has twice the sensitivity of the uncombined pixels. Alternatively, horizontally combining the measured values, (either voltage or digital) from same colored pixels in FIG. 4A in groups of four produces the combined pixels with combined signals R′, G′, and B′ shown in FIG. 7B. In this case, since the signal increases by a factor of four but the noise increases by 2, each R′, G′, and B′ has twice the sensitivity of the uncombined pixels. In another alternative combination scheme, vertically combining the charge from same colored pixels in groups of two as in FIG. 7A, and horizontally summing or averaging the measured values of the combined pixels of FIG. 7A in groups of four produces the final combined color pixels of FIG. 7C, with R″, G″, and B″ representing the final combinations of same colored pixels. In this combination arrangement, the final combined color pixels of FIG. 7C each have four times the sensitivity of the uncombined pixels. Some sensor architectures, notably certain CCD arrangements, can permit the charge from all eight same colored pixels within each cell to be combined in the fashion of FIG. 7C, leading to an eightfold increase in sensitivity for the combined color pixels.

From the foregoing, it will now be understood that there are several degrees of freedom in combining color pixels for the purpose of adjusting the photosensitivity of the color pixels. Well known combining schemes will suggest themselves to one skilled in the art and is based on scene content, scene illuminant, overall light level, or other criteria. Furthermore, the combining scheme is selected to deliberately permit the combined pixels to have either less sensitivity or more sensitivity than the panchromatic pixels.

To this point the image sensor has been described as employing red, green, and blue filters. The present invention is practiced with alternative filter selections. Image sensors employing cyan, magenta, and yellow sensors are well known in the art, and the present invention is practiced with cyan, magenta, and yellow color filters. FIG. 8A shows the cyan, magenta, and yellow equivalent of FIG. 4A, with C representing cyan pixels, M representing magenta pixels, and Y representing yellow pixels. The present invention is also usable with pixels having more than three color photoresponses.

FIG. 8B shows a minimal repeating unit of the present invention that includes cyan pixels (represented by C), magenta pixels (represented by M), yellow pixels (represented by Y), and green pixels (represented by G). This retains the overall cell arrangement of the minimal repeating unit shown in FIG. 5, but includes four different colored pixels and therefore four different colored corresponding cells. FIG. 8C shows yet another alternative four color arrangement including red pixels (represented by R), blue pixels (represented by B), green pixels with one color photoresponse (represented by G), and alternative green pixels with a different color photoresponse (represented by E). FIG. 8D shows yet another alternative four color arrangement, wherein one of the green cells of FIG. 4A is replaced by a yellow cell, with the yellow pixels represented by Y.

The present invention is practiced with fewer than three colors in addition to the panchromatic pixels. For example, a minimal repeating unit with cells corresponding to the colors red and blue is suitable for use.

Many alternatives to FIG. 4A are practiced within the spirit of the present invention. For example, FIG. 9 represents an alternative minimal repeating unit of the present invention with the same cell structure as FIG. 4A but with a checkerboard pattern of panchromatic pixels. This pattern provides uniform panchromatic sampling of the image, overcoming the vertical panchromatic sampling deficit of FIGS. 4A, 4C, and 4D. FIG. 9 is characterized as an example of practicing the present invention by arranging the panchromatic pixels in diagonal lines. FIG. 9 is further characterized as having single diagonal lines of panchromatic pixels with each diagonal line separated from a neighboring diagonal line of panchromatic pixels by a diagonal line of color pixels. Yet another characteristic of FIG. 9 is that groups two or more of same color pixels are arranged side by side in diagonal lines.

The patterns presented so far have had equal numbers of panchromatic and color pixels. The present invention is not limited to this arrangement as there are more panchromatic pixels than color pixels. FIG. 10A shows yet another embodiment of the present invention wherein color pixels are embedded within a grid pattern of panchromatic pixels. This pattern provides very good panchromatic spatial sampling while expressing the same color cell arrangement as FIGS. 4A and 9. FIG. 10B provides an example of a four color embodiment of the panchromatic grid pattern. In general, the minimal repeating unit of FIG. 10 is characterized as separating each color pixel from a neighboring color pixel by one or more panchromatic pixels.

For a given pixel pattern, a minimal repeating unit has been previously defined as a repeating unit such that no other repeating unit has fewer pixels. In the same sense, the sizes of repeating units from different pixel patterns are compared according to the total number of pixels in the repeating unit. As an example, a four pixel by eight pixel repeating unit from one pixel pattern is smaller than a six pixel by six pixel repeating unit from another pixel pattern because the total number of pixels (4×8=32) in the first repeating unit is smaller than the total number of pixels (6×6=36) in the second repeating unit. As a further example, a repeating unit that is smaller than a repeating unit having eight pixels by eight pixels contains fewer than 64 total pixels.

All the patterns presented so far have exhibited a cell structure wherein each cell contains a single color in addition to panchromatic pixels. Furthermore, all the patterns presented so far have exhibited a minimal repeating unit that is eight by eight pixels in extent. A minimal repeating unit can also be used that has cells with more than one color in each cell; also, a minimal repeating unit is defined that is less than eight pixels by eight pixels in extent. For example, the minimal repeating unit of FIG. 11A has two cells with each cell including two colors: blue and green (represented by B and G respectively) in the left cell, and red and green (represented by R and G respectively) in the right cell. In FIG. 11A the cells contain two colors, and these colors are arranged to facilitate combining same colors for the purpose of improving color sensitivity. FIG. 11B shows how the minimal repeating unit of FIG. 11A is tiled in order to stagger the red and blue colors. FIG. 11C provides a minimal repeating unit employing four colors and two colors per cell. FIG. 11D shows how the minimal repeating unit of FIG. 11C is tiled in order to stagger the red and blue colors. In FIG. 11D the coarse color pattern is characterized as a checkerboard of two different color photoresponses in the green range (represented by G and E) interleaved with a checkerboard of red and blue (represented by R and B, respectively). FIG. 12A provides a panchromatic checkerboard version of FIG. 11A, and FIG. 12B provides a panchromatic checkerboard version of FIG. 11C. In general, the minimal repeating units of FIGS. 11A and 11C are characterized as separating each color pixel from a neighboring color pixel in rows and columns by a dissimilar pixel, either a different color pixel or a panchromatic pixel.

The minimal repeating units described so far have been eight by eight or four by eight pixels in extent. However, the minimal repeating unit is smaller. For example, FIG. 13A is analogous to FIG. 4A, but with each color cell being 3 pixels wide by 4 pixels high and with the overall minimal repeating unit being 6 pixels wide by 8 pixels high. FIG. 13B eliminates two of the color pixel rows from FIG. 13A, thereby producing cells that are 3 pixels by 3 pixels and a minimal repeating unit that is 6 pixels by 6 pixels. FIG. 13C goes further by eliminating two of the panchromatic rows, thereby producing cells that are 3 pixels wide by 2 pixels high (with each cell containing 3 panchromatic pixels and 3 color pixels) and a minimal repeating unit that is 6 pixels wide by 4 pixels tall. The patterns shown in FIGS. 13A through 13C are particularly usable if the scheme for combining colors within each cell requires less than the numbers of pixels shown in FIG. 4A and other patterns.

FIG. 14A shows yet another minimal repeating unit. The minimal repeating unit in FIG. 14A is six pixels by six pixels, with each cell including a 4 pixel diamond pattern of a single color with the remaining 5 pixels being panchromatic pixels. The panchromatic spatial sampling pattern shown in FIG. 14A is somewhat irregular, suggesting the pattern of FIG. 14B with a panchromatic checkerboard and the remaining pixels in each three pixel by three pixel cell occupied by a single color.

FIG. 15A shows a minimal repeating unit that is four by four pixels and includes four two by two pixel cells. Note that each cell includes two panchromatic pixels and two same color pixels. The invention requires the placement of two same color pixels in each of the two by two cells in order to facilitate combining the color pixels within each cell. FIG. 15B is similar to FIG. 15A but employs a panchromatic checkerboard pattern.

Methods of controlling exposure were described earlier, including controlling integration time electronically at the image sensor. In the context of the present invention, this method of controlling exposure provides an additional way to overcome the disparity between the photosensitivity of the panchromatic pixels and the photosensitivity of the color pixels. By providing one integration time for the panchromatic pixels and a different integration time for the color pixels, the overall exposure for each group of pixels can be optimized. Generally, the color pixels will be slower than the panchromatic pixels, so a longer integration time can be applied to the color pixels than to the panchromatic pixels. Furthermore, different integration times can be applied to each color of the color pixels, allowing the exposure for each color to be optimized to the current scene capture conditions. For example, light from a scene illuminated by an incandescent light source contains red light in relatively higher amounts than green and blue light; in this case, the integration times for green and blue pixels can be made longer and the integration time for red pixels can be made shorter to compensate for the relative abundance of red light.

Turning now to FIG. 16, the minimal repeating unit of FIG. 5 is shown subdivided into four cells, a cell being a contiguous subarray of pixels having fewer pixels than a minimal repeating unit. The software needed to provide the following processing is included in DSP 36 of FIG. 1. Cells 220, 224, 226, and 228 are examples of cells wherein these cells contain pixels having green, red, blue and green photoresponses, respectively. In this example, cell 220 contains both panchromatic pixels and green pixels, the green pixels being identified as pixel group 222. The eventual goal is to produce a single green signal for cell 220 by combining the eight green signals from the green pixels in pixel group 222. Depending on the image sensor's mode of operation, a single green signal is produced by combining all eight green signals in the analog domain (e.g. by charge binning), or multiple green signals are produce by combining smaller groups of pixels taken from pixel group 222. The panchromatic pixels of cell 220 are shown in FIG. 17A. In the following examples, all eight signals from these panchromatic pixels are individually digitized. The green pixels of cell 220 are shown in FIGS. 17B-17E wherein they are grouped together according to how their signals are combined in the analog domain. FIG. 17B depicts the case in which all eight green pixels are combined to produce a single green signal for cell 220 (FIG. 16). The sensor can produce two green signals, for example, by first combining the signals from pixels G21, G22, G23, and G24, and then combining the signals from pixels G41, G42, G43, and G44, as shown in FIG. 17C. Two signals are produced in other ways as well. The sensor can first combine signals from pixels G21, G22, G41, and G42, and then combine signals from pixels G23, G24, G43, and G44, as shown in FIG. 17D. The sensor can also produce four green signals for cell 220 by combining four pairs of signals, for example, combining pixels G21 with G22, then combining G23 with G24, then combining G41 with G42, and finally combining G43 with G44, as shown in FIG. 17E. It is clear that there are many additional ways to combine pairs of green signals within cell 220 (FIG. 16). If the sensor does no combining at all, then all eight green signals are reported individually for cell 220. Thus, in the case of cell 220, the sensor can produce one, two, four or eight green values for cell 220, and produce them in different ways, depending on its mode of operation.

For cells 224, 226, and 228 (FIG. 16), similar color signals are produced by the sensor depending on its mode of operation. The color signals for cells 224, 226, and 228 are red, blue, and green, respectively.

Returning to the case of cell 220, regardless of how many signals are digitized for this cell, the image processing algorithm of the present invention further combines the digitized green values to produce a single green value for the cell. One way that a single green value is obtained is by averaging all the digitized green values produced for cell 220. In the event that a cell contains color pixels of differing photoresponses, all the color data within the cell is similarly combined so that there is a single value for each color photoresponse represented within the cell.

It is important to distinguish between the color values pertaining to pixels in the original sensor that captured the raw image data, and color values pertaining to cells within the original sensor. Both types of color values are used to produce color images, but the resulting color images are of different resolution. An image having pixel values associated with pixels in the original sensor is referred to as a high-resolution image, and an image having pixel values associated with cells within the original sensor is referred to as a low-resolution image.

Turning now to FIG. 18, the digital signal processor block 36 (FIG. 1) is shown receiving captured raw image data from the data bus 30 (FIG. 1). The raw image data is passed to both the Low-resolution Partial Color block 202 and the High-resolution Panchrome block 204. An example of a minimal repeating unit for an image sensor has already been shown in FIG. 5 and FIG. 16. In the case of cell 220 (FIG. 16), the captured raw image data includes the panchromatic data that is produced by the individual panchromatic pixels as shown in FIG. 17A. Also, for cell 220 (FIG. 16), one or more green (color) values are also included, for example, from the combinations shown in FIGS. 17B-E.

In the Low-resolution Partial Color block 202 (FIG. 18), a partial color image is produced from the captured raw image data, a partial color image being a color image wherein each pixel has at least one color value and each pixel is also missing at least one color value. Depending on the sensor's mode of operation, the captured raw data contains some number of color values produced by the color pixels within each cell. Within the Low-resolution Partial Color block 202, these color values are reduced to a single value for each color represented within the cell. For the cell 220 (FIG. 16), as an example, a single green color value is produced. Likewise, for cells 224, 226 and 228, a single red, blue and green color value is produced, respectively.

The Low-resolution Partial Color block 202 processes each cell in a similar manner resulting in an array of color values, one for each cell. Because the resulting image array based on cells rather than pixels in the original sensor, it is four times smaller in each dimension than the original captured raw image data array. Because the resulting array is based on cells and because each pixel has some but not all color values, the resulting image is a low-resolution partial color image. At this point, the low-resolution partial color image is color balanced.

Looking now at the High-resolution Panchrome block 204, the same raw image data is used as shown in FIG. 16, although the only the panchromatic values will be used (FIG. 17A). This time the task is to interpolate a complete high-resolution panchromatic image by estimating panchromatic values at those pixels not having panchromatic values already. In the case of cell 220 (FIG. 16), panchromatic values must be estimated for the green pixels in pixel group 222 (FIG. 16). One simple way to estimate the missing panchromatic values is to do vertical averaging. Thus, for example, we can estimate the panchromatic value at pixel 22 as follows:

P22=(P12+P32)/2

An adaptive method can also be used. For example, one adaptive method is to compute three gradient values and take their absolute values:

SCLAS=ABS(P31−P13)
VCLAS=ABS(P32−P12)
BCLAS=ABS(P33−P11)

using the panchromatic values are shown in FIG. 17A. Likewise, three predictor values are computed:

SPRED=(P31+P13)/2
VPRED=(P32+P12)/2
BPRED=(P33+P11)/2

Then, set P22 equal to the predictor corresponding to the smallest classifier value. In the case of a tie, set P22 equal to the average the indicated predictors. The panchromatic interpolation is continued throughout the image without regard to cell boundaries. When the processing of High-resolution Panchrome block 204 is done, the resulting digital panchromatic image is the same size as the original captured raw image, which makes it a high-resolution panchromatic image.

The Low-resolution Panchrome block 206 receives the high-resolution panchromatic image array produced by block 204 and generates a low-resolution panchromatic image array which is the same size as the low-resolution partial color image produced by block 202. Each low-resolution panchromatic value is obtained by averaging the estimated panchromatic values, within a given cell, for those pixels having color filters. In the case of cell 220 (FIG. 16) the high-resolution panchromatic values, previously estimated for the green pixels in pixel group 222 (FIG. 16), are now averaged together to produce a single low-resolution panchromatic value for the cell. Likewise, a single low-resolution panchromatic value is computed for cell 224 using high-resolution panchromatic values estimated at the pixels having red filters. In this manner, each cell ends up with a single low-resolution panchromatic value.

The Low-resolution Color Difference block 208 receives the low-resolution partial color image from block 202 and the low-resolution panchrome array from block 206. A low-resolution intermediate color image is then formed by color interpolating the low-resolution partial color image with guidance from the low-resolution panchrome image. The exact nature of the color interpolation algorithm, to be discussed in detail later, depends on which pattern of pixel photoresponses was used to capture the original raw image data.

After the low-resolution intermediate color image is formed it is color corrected. Once the low-resolution intermediate color image is color corrected, a low-resolution image of color differences are computed by subtracting the low-resolution panchromatic image from each of the low-resolution color planes individually. The High-Resolution Color Difference block 210 receives the low-resolution color difference image from block 208 and, using bilinear interpolation, upsamples the low-resolution color difference image to match the size of the original raw image data. The result is a high-resolution color difference image that is the same size as the high-resolution panchromatic image produced by block 204.

The High-resolution Final Image block 212 receives the high-resolution color difference image from block 210 and the high-resolution panchromatic image from block 204. A high-resolution final color image is then formed by adding the high-resolution panchromatic image to each of the high-resolution color difference planes. The resulting high-resolution final color image can then be further processed. For example, it is stored in the DSP Memory block 32 (FIG. 1) and then sharpened and compressed for storage on the Memory Card block 64 (FIG. 1).

The sensor filter patterns shown in FIGS. 4A-D, 8A, 9, 10A, 13A-C, 14A-B and 15A-B have a minimal repeating unit such that the resulting low-resolution partial color image, produced in block 202, exhibits the repeating Bayer pattern for color filters:

- G R
- B G
  
  In addition to a single color value, given by the low-resolution partial color image, every cell also has a panchromatic value given by the low-resolution panchromatic image.

Considering the case in which the Bayer pattern is present in the low-resolution partial color image, the task of color interpolation within the Low-resolution Color Differences block 208 (FIG. 18) can now be described in greater detail. Color interpolation begins by interpolating the green values at pixels not already having green values, shown as pixel 234 in FIG. 19A. The four neighboring pixels, shown as pixels 230, 232, 236, and 238, all have green values and they also all have panchromatic values. The center pixel 234 has a panchromatic value, but does not have a green value as indicated by the question marks.

The first step is to compute two classifier values, the first relating to the horizontal direction, and the second to the vertical direction:

HCLAS=ABS(P4−P2)+ABS(2*P3−P2−P4)
VCLAS=ABS(P5−P1)+ABS(2*P3−P1−P5)

Then, compute two predictor values, the first relating to the horizontal direction, and the second to the vertical direction:

HPRED=(G4+G2)/2+(2*P3−P2−P4)/2
VPRED=(G5+G1)/2+(2*P3−P1−P5)/2

Finally, letting THRESH be an empirically determined threshold value, we can adaptively compute the missing value, G3, according to:

IF MAX( HCLAS, VCLAS ) < THRESH G3 = ( HPRED + VPRED )/2ELSEIF VCLAS < HCLAS G3 = VPREDELSE G3 = HPREDEND

Thus, if both classifiers are smaller than the threshold value, an average of both predictor values is computed for G3. If not, then either HPRED or VPRED is used depending on which classifier HCLAS or VCLAS is smaller.

Once all the missing green values have been estimated, the missing red and blue values are interpolated. As shown in FIG. 19B, pixel 242 is missing a red value but its two horizontal neighbors, pixels 240 and 244, have red values R2 and R4 respectively. All three pixels have green values. Under these conditions, an estimate for the red value (R3) for pixel 242 is computed as follows:

R3=(R4+R2)/2+(2*G3−G2−G4)/2

Missing blue values are computed in a similar way under similar conditions. At this point, the only pixels that still have missing red and blue values are those requiring vertical interpolation. As shown in FIG. 19C, pixel 252 is missing a red value and its two vertical neighbors, pixels 250 and 254, have red values R1 and R5 respectively. Under these conditions, an estimate for the red value (R3) for pixel 252 is computed as follows:

R3=(R5+R1)/2+(2*G3−G1−G5)/2

Missing blue values are computed in a similar way under similar conditions. This completes the interpolation of the low-resolution partial color image and the result is a low-resolution intermediate color image. As described earlier, the low-resolution color differences can now be computed by subtracting the low-resolution panchrome values from each color plane: red, green, and blue in the example just discussed.

Not all sensors produce low-resolution partial color images exhibiting a repeating Bayer pattern of color values. For example, the sensor pattern shown in FIG. 11A determines that each cell receives two color values: either green and red, or green and blue. Consequently, in this case, the color interpolation task within the Low-resolution Color Differences block 208 (FIG. 18) estimates missing values of red or missing values of blue for each pixel. Referring to FIG. 19D, a pixel 264 is shown having a green value (G3) but not having a red value (R3). Four of the neighboring pixels 260, 262, 266, and 268 have green values and red values. The method for interpolating the red value for pixel 264 (FIG. 19D) is similar to the method used to interpolate the green value for pixel 234 (FIG. 19A).

The first step is to compute two classifier values, the first relating to the horizontal direction, and the second to the vertical direction:

HCLAS=ABS(G4−G2)+ABS(2*G3−G2−G4)
VCLAS=ABS(G5−G1)+ABS(2*G3−G1−G5)

Then, compute two predictor values, the first relating to the horizontal direction, and the second to the vertical direction:

HPRED=(R4+R2)/2+(2*G3−G2−G4)/2
VPRED=(R5+R1)/2+(2*G3−G1−G5)/2

Finally, letting THRESH be an empirically determined threshold value, the missing value G3 is computed adaptively according to:

IF MAX( HCLAS, VCLAS ) < THRESH R3 = ( HPRED + VPRED )/2ELSEIF VCLAS < HCLAS R3 = VPREDELSE R3 = HPREDEND

Thus, if both classifiers are smaller than the threshold value, an average of both predictor values is computed for R3. If not, then either HPRED or VPRED is used depending on which classifier HCLAS or VCLAS is smaller.

The missing blue values are interpolated in exactly the same way using blue values in place of red. Once completed, the low-resolution intermediate color image has been produced. From there, the low-resolution color differences are computed as previously described.

The invention has been described in detail with particular reference to certain preferred embodiments thereof, but it will be understood that variations and modifications are effected within the spirit and scope of the invention.

PARTS LIST

10 light from subject scene

11 imaging stage

12 lens

13 filter assembly

14 iris

16 brightness sensor

18 shutter

20 image sensor

22 analog signal processor

24 analog to digital (A/D) converter

26 timing generator

28 image sensor stage

30 digital signal processor (DSP) bus

32 digital signal processor (DSP) memory

36 digital signal processor (DSP)

38 processing stage

40 exposure controller

50 system controller

52 system controller bus

54 program memory

56 system memory

57 host interface

60 memory card interface

62 memory card socket

64 memory card

68 user control and status interface

70 viewfinder display

72 exposure display

74 user inputs

76 status display

80 video encoder

82 display controller

88 image display

100 minimal repeating unit for Bayer pattern

102 repeating unit for Bayer pattern that is not minimal

110 spectral transmission curve of infrared blocking filter

112 unfiltered spectral photoresponse curve of sensor

114 red photoresponse curve of sensor

116 green photoresponse curve of sensor

118 blue photoresponse curve of sensor

120 first green cell

122 red cell

124 blue cell

126 second green cell

202 low-resolution partial color block

204 high-resolution panchromatic block

206 low-resolution panchromatic block

208 low-resolution color differences block

210 high-resolution color differences block

212 high-resolution final image block

220 first green cell

222 green pixels in first green cell

224 red cell

226 blue cell

228 second green cell

230 upper pixel values for interpolating missing green value

232 left pixel values for interpolating missing green value

234 pixel with missing green value

236 right pixel values for interpolating missing green value

238 lower pixel values for interpolating missing green value

240 left pixel values for interpolating missing red value

242 pixel with missing red value

244 right pixel values for interpolating missing red value

250 upper pixel values for interpolating missing red value

252 pixel with missing red value

254 lower pixel values for interpolating missing red value

260 upper pixel values for interpolating missing red value

262 left pixel values for interpolating missing red value

264 pixel with missing red value

266 right pixel values for interpolating missing red value

268 lower pixel values for interpolating missing red value

Capturing images under varying lighting conditions

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CPC

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