Patent Application
20110063201
Displays and display technology are used for a variety purposes. For example, displays are used for traditional uses such as watching television or in conjunction with a computer for viewing and manipulating data. Additionally, display technology has been implemented in a variety of mobile components, such as mobile telephones, that are increasingly used for both communication and as a multi-media tool.
A common type of display used in a variety of applications is a liquid crystal display (LCD). LCDs are typically thin, flat panels that may be manufactured to fit a variety of size and space parameters and whose common specifications and components are known. Power consumption for LCDs is, however, a concern as LCDs are both being used in more mobile, battery powered devices as well as being formed for larger displays. The backlight used for the LCD is often the component of the LCD with the highest power consumption. Light emitting diode (LED) backlights are one type of backlight that currently allows for the most optimal display and definition when using an LCD.
Additionally, red-green-blue (RGB) LEDs and/or white LEDs may be used in an LCD to generate a high number of colors. Further, the red, green and blue (RGB) LEDs, white LEDs or any other combination of LEDs can be arranged in a specified structure (e.g. grid structure) behind or beside a pixel plane of the LCD and may be driven by pulse width modulation (PWM) in a process known as local dimming, as desired by the properties of the image that is being displayed.
In order to achieve a properly displayed image at a lower power consumption, the brightness of the LEDs must be accurately calculated. The brightness of the LEDs can be referred to as PWM values and, based upon these values, an image can be displayed with varying color and contrast. However, some current methods of calculating PWM values rely on a series of approximation algorithms for image processing. These algorithms use filter functions and a variety of complex mathematical operations and iterations to find approximate solutions to downsize a high resolution source image in order to determine values of a low resolution LED grid. The approximate solutions for the PWM values, however, result in the LED backlight using more power than necessary and can cause flaws in an image to be displayed on the LCD, such as lower image resolution and clipping. Additionally, the complex nature of the approximation algorithms facilitates the use of more complex, expensive hardware to perform the approximations. Further, because of the time needed to make the calculations, the process is slower which can lead to problems in displaying video content, for example the display of video at a less desirable frame rate.
A method, system and apparatus for displaying an image on a liquid crystal display. The method can include, in some exemplary embodiments, steps for calculating a luminance for pixels in an image in a liquid crystal display (LCD) based upon a light spread function and brightness values of light emitting diodes (LEDs); changing a brightness value of an LED based upon a consideration of a gray value of the pixels and a distance of the pixels from a dominant LED; and setting the brightness value of the LEDs units to a brightness value substantially greater than or equal to a gray value of each pixel of the image.
In other exemplary embodiments, a liquid crystal display may be described. The liquid crystal display can include a plurality of pixels to display an image; a backlight with a plurality of light emitting diodes; and a processor that processor calculates a luminance for the plurality of pixels in an image in the liquid crystal display, changes a brightness of a light emitting diode based upon a consideration of a gray value of a number of the plurality of pixels and a distance of the number of the plurality of pixels from a dominant light emitting diode and sets the brightness of the plurality of light emitting diodes to a brightness at least equal to the gray value of the plurality of pixels in the image.
In still other exemplary embodiments, a system for providing an image on a liquid crystal display may be described. The system may include a plurality of pixels that display an image on a liquid crystal display (LCD); a backlight having a plurality of light emitting diodes that light the image; and at least one processor that calculates a luminance for pixels in an image in a LCD based upon a light spread function and brightness values of light emitting diodes (LEDs), changes a brightness of an LED based upon a consideration of the gray value of the pixels and the distance of the pixels from a dominant LED and sets the brightness of the LED units to a brightness substantially greater than or equal to a gray value of each pixel of the image.
Advantages of embodiments of the present invention will be apparent from the following detailed description of the exemplary embodiments thereof, which description should be considered in conjunction with the accompanying drawings in which:
Aspects of the invention are disclosed in the following description and related drawings directed to specific embodiments of the invention. Alternate embodiments may be devised without departing from the spirit or the scope of the invention. Additionally, well-known elements of exemplary embodiments of the invention will not be described in detail or will be omitted so as not to obscure the relevant details of the invention. Further, to facilitate an understanding of the description discussion of several terms used herein follows.
The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments. Likewise, the term “embodiments of the invention” does not require that all embodiments of the invention include the discussed feature, advantage or mode of operation.
Generally referring to
The coefficients aij(k) can model the spread of the light emitted from the k-th LED on its way to pixel (ij). As the LEDs can be driven by pulse width modulation (PWM), each LED may be driven to have a fixed luminance for a predetermined amount of time. For example, the duty cycle x(k) can lie between 0 and 100% and can determine the fraction of time when the k-th LED may shine with a fixed luminance. The power consumption can then be proportional to the sum of duty cycles. Thus, through a minimization of the sum of all of the PWM values, a minimization of power consumption may be realized, as shown below in Equation 2:
The boundary condition that the solution is desired to be clipping-free may then be described in a system of inequalities as shown in Equation 3:
Here matrix A can be made of aij(k) and can capture the light spread model of the backlights and r represents exemplary gray values for a given image. However, when displaying an image or images, such as video, in high definition, the above system of inequalities can have more two million inequalities with more than one hundred variables of x. Therefore it may be difficult to determine an optimal solution that utilizes a minimal amount of power for this problem in real time, causing clipping, this may mean that at least one of the inequalities is not fulfilled, amongst other problems, in the resulting displayed image. Therefore, the present method, system and apparatus, in one exemplary embodiment, provide a faster approximation algorithm that can provide a nearly optimal solution assuring minimum power consumption.
Referring back to
Referring now to
In exemplary
Exemplary
Still referring to
In one exemplary embodiment, and as shown in the exemplary chart of
Similarly, for pixels that may be influenced by two or more LEDs, the above equation may be modified. For example, for each LED that may dominate a pixel, an inequality may be derived by setting variable of other LEDs x(l) for l≠k to an image-independent predetermined value pre(l):
In this exemplary embodiment, all of the LEDs x(l) except for the actual considered LED x(k) may be set to their predetermined values pre(l) and the result of their superposition may be subtracted to the pixel value. Further, for a lower computation effort using Equation 5, the LEDs of the LED group associated with the pixel may be taken into account where other LEDs may be discounted. Thus, the amount of processing needed may be significantly reduced.
The predetermined LED values pre(l) may be any value, for example upper bounds of a PWM duty cycle or an estimate thereof. In some exemplary embodiments where the upper bounds may be used as the predetermined values, the inequality of Equation 5 may yield lower bounds for the duty cycle values insofar as the duty cycles of the LEDs may be at least the lower respective bounds, which may further yield clipping-free image quality.
In further exemplary embodiments, a simple preset or predetermined value for LEDs x(l) that yields lower bounds may be a maximum duty cycle. Additionally, tighter upper bounds may be given by an optimum representation of an image, for example where an image to be displayed is significantly (question: what is the meaning of significantly?) white. Thus, for an exemplary layout and light spread model, the summation of Equation 5 may be pre-calculated and stored in a memory, either externally by a computer, by the local dimming processor directly or in any other available manner. Thus, the summation of Equation 5, Σl≠kaij(l)·pre(l), may be read from the memory and used for Equation 5 as a first phase (phase 502) for any or every image displayed on a display. Referring back to
Using Equation 5 and using the assumption that the brightness of an LED may affect every pixel of an image, a value for a specific LED (e.g. x(k)) may be determined when the values of the other LEDs (e.g. x(l)) are set, as stated above with respect to Equation 5. Using this process, considering any pixel correlated to a LED (e.g. k-th LED), could yield a new x(k) according to Equation 5. The inequality can say that the LED value x(k) can be increased and the previous or “older” LED value can be overwritten by this new, higher LED value. Otherwise, if the “newer” LED value is lower than the “older” x(k), the older x(k) remains valid. Thus the pixels covered previously can remain covered as the new LED values that are determined can continue to be higher. Then previously covered pixels may not need to be reconsidered and, following a screening of every pixel, a complete phase can be completed.
Thus, using the above-described methodology and referring to an exemplary first phase (phase 502) of
In a further exemplary embodiment, if the total number of pixels is too large and could result in a slower than desired processing speed, a smaller sample size may be used to determine the assignment of the first phase (phase 502). The use of a smaller sample size may allow for increased processing speeds and may not void any lower bound properties.
Further, during the first phase (phase 502), information may be collected, computed or otherwise gained that may be utilized in later phases, for example phases 504 and 506, as desired. For example, a factor by which the duty cycles may be multiplied to prevent clipping may be determined. Additionally, this additional information can be gained from an LED group or a single LED.
At the completion of phase one (phase 502), an assignment of LED brightness may be made to the desired LEDs. However, in some exemplary embodiments, some pixels may not be considered during phase one (phase 502), which may allow for an increased processing speed. Depending on the information gathered from any number of pixels that may have been considered, however, imperfections or undesired display effects may remain. However, as shown in the following exemplary embodiments, further processing or iterative phases may be utilized to achieve a desired image result. Additionally, any desired number of further iterative phases may be added which may allow smaller incremental increases in the LED values, while in the second phase (506) the LED values may be fully increased, as may be shown below. The addition of iterative phases can yield an increased power savings over fewer iterations. However, as the addition of further iterative phases may increase processing time, the number of iterative phases may be varied so as to provide for an ideal or desired power savings and processing speed.
In a second exemplary phase, phase 506, as shown in
Equation 6 differs from Equation 5 insofar as the actual assignment of x(l), which can be image-dependent, may now be used and, for the start, x(l) can be an output or assignment of the first phase (phase 502). Further, as the LEDs may be interdependent, each LED group may need to be considered as described previously, for example with regards to the assignment of the pixels to a LED group described previously. Following a screening of a complete image, the second phase (phase 506) may be completed.
As discussed previously, the luminance of a pixel can be affected by four or more LEDs. Therefore, to cover the gray value of a pixel, the LEDs that surround or influence a pixel may be varied or adjusted in brightness. Additionally, at the start of the second phase (phase 506), the intensities of the LEDs may be at their lower bounds but any underestimation of the final effect of the LEDs on surrounding pixels is minimized through the known decay of influence of LEDs on remotely located pixels, as discussed previously.
Also as discussed earlier, the Am,k of other LEDs may be set to zero to reduce complexity and processing time. However, in further exemplary embodiments where the brightness of an LED group may be calculated, the effect of other LEDs with a non-zero Am,k may also be considered. The brightness of these newly considered LEDs may not be updated, however as only the actual assignments can be used. Thus, the matrix of Equation 3 may still be considered a sparse matrix and the computation may be performed, as shown with respect to exemplary
In exemplary
As shown in
In exemplary
The grouping of LEDs, for example a group of 4 LEDs, can employ the fact that, for many displays, the backlight can have many LED units, e.g. 100, and the light spread matrix may be sparse. The updating of LED brightness's one LED group at one time can yield a local optimization result which may be close to the result of the global optimization. However the computation effort of the processor may be much lower. For some displays, such as smaller displays and displays with edge light, the number of LED units may be much lower, for example 3, 6 or 10, and the light spread matrix may be not as sparse. Therefore grouping of a part of LED units may not reduce the computation effort considerably and the power consumption may still be considerably higher than the optimum. However the luminance of each pixel may remain dominated by its closest LED unit and this may be used for the global optimization. Thus the pixels can be considered in the same or similar sequence as illustrated by
In a further exemplary embodiment and referring to the intermediate phase (phase 504) of
In some alternative embodiments, if an intermediate phase 504 iterates until there are no deficient pixels remaining, a final assignment for the brightness of the LEDs may be determined. As a result, the second phase 504 described above may be considered unnecessary. However, if deficient pixels remain after a predefined number of iterations of an intermediate phase 504 are performed, the second phase 506 may proceed as described previously. With either process, the brightness of the LEDs in the display may be determined to be at an optimal level and clipping-free boundary conditions may be established.
In further exemplary embodiments, an image may be condensed, for example prior to either a first phase (phase 502) and/or a second phase (phase 506). For example an array of about 20×15 pixels (or pixel values) may be condensed to one or more values. Such an array may be condensed by a variety of methods, for example by taking the average, median, maximum or any combination of values. In addition to this gray value for a new concentrated pixel, further values or numbers may be added to describe this concentrated pixel. For example, the condensing function that is used may depend on the content of the pixel array to be condensed. Also, the function may be coded as a number or value. Thus, a new image formed of the concentrated pixels with a lower pixel number may be presented. Then the light spread function can describe a relationship between the concentrated pixels and the brightness of the LEDs. The resultant processing and screen of a lower number of pixels may allow for the use of a simpler or lower cost processor while also increasing the processing speed of a display. Further, when desired, image enhancing techniques such as image enhancement and the like as well as further power saving techniques e.g. the reduction of the amplitude for high spatial frequency may be implemented when condensing pixels. Further, if the final LED values are known or available, the luminance of every original pixel may be determined or calculated as well as the transmission values of the LCD pixels and the calculation may also depend on the code for the condensing function and/or further values or numbers of the concentrated pixel corresponding to an LCD pixel.
In still another exemplary embodiment, an LED backlight may experience local dimming. In these examples, it may be desirable to determine the transmission values of the thin film transistor (TFT) pixels of the display. Using Equation 1, the luminance produced by any LEDs at a pixel location ij (Bij) may be calculated. Then the TFT pixel values tij may be calculated using Equation 7:
This calculation may, in some exemplary embodiments, be considered post-processing as the methodology described herein can efficiently calculate LED values as based upon the content of an image to be displayed. Also image enhancing techniques and/or further power saving techniques may be implemented in this post-processing phase. Additionally, the output of the post-processing can be stored in a memory and further can be used to control or drive the TFT pixels.
In another exemplary embodiment, and as shown in the exemplary flowchart of
Further, in step 902 the setup for the following calculations may be performed. The backlight board information e.g. the numbers and locations of the LEDs may be read, so that pixels may be assigned to an LED group and to their dominating LEDs. In addition, the light spread function of the LEDs and the predetermined LED values may be read and used to calculate the summation of Equation 5 Σl≠kaij(l)·pre(l) values which may also be stored in a RAM. In step 902, a sequence of LED groups starting from a corner or edge of a display, along with a sequence of pixel starting from a proximate pixel to an LED and followed by more distant pixels may be designated. Additionally, it may be noted that any of the data involved with step 902 may be set, measured or calculated in a computer or by a processor that may be separate from a processor associated with a display. For example, this data can be stored in read-only memory (ROM) so that a processor associated with a display may not be utilized for such processing.
Still referring to
The foregoing description and accompanying drawings illustrate the principles, preferred embodiments and modes of operation of the invention. However, the invention should not be construed as being limited to the particular embodiments discussed above. Additional variations of the embodiments discussed above will be appreciated by those skilled in the art.
Therefore, the above-described embodiments should be regarded as illustrative rather than restrictive. Accordingly, it should be appreciated that variations to those embodiments can be made by those skilled in the art without departing from the scope of the invention as defined by the following claims.
