The present invention relates generally to contrast enhancement and, more particularly, to a method for generating transfer curves for adaptive contrast enhancement.
Traditional contrast adjustment methods in displays and TVs do not take into account the input image content and result in unintended average brightness shifts as well as saturation or clipping. For example, poor results are obtained when increasing the contrast on an image that already has good contrast, and poor contrast is obtained when the image has a large portion of very bright or very dark pixels. Similarly, decreasing the contrast in a non-adaptive approach will “black out” images that already have poor contrast.
Therefore, what is desired is a contrast enhancement method that takes into account the input image content and avoids the above problems.
What is provided, therefore, is an adaptive contrast enhancement method that takes into account the content of the input image and uses transfer curves to alter pixel luminances. The method generates transfer curves that enhance the bright pixels in mostly dark images and enhance the dark pixels in mostly bright images.
For a dark image, a transfer curve is generated which increases luminance in high-luminance regions of the image without substantially changing the luminance in the mid- and low-luminance regions of the image. For a bright image, a transfer curve is generated which decreases the luminance in the dark areas of the image without substantially changing the luminance in the mid- and high-luminance regions of the image. For a medium-bright image, a transfer curve is generated with increases the luminance in the high-luminance range and decreases the luminance in the low-luminance range of the histogram without substantially changing the luminance in the medium-luminance range of the image.
The present invention is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which like reference numerals refer to similar elements and in which:
a shows an example medium-bright image and a histogram for the image, in accordance with an embodiment of the present invention.
b shows an example dark (low-brightness) image and a histogram for the image, in accordance with an embodiment of the present invention.
c shows three example luminance ranges, in accordance with an embodiment of the present invention.
a shows a histogram for a dark image, and
c is a low-luminance image showing two actors wearing dark suits and bright shirts, in accordance with an embodiment of the present invention.
a shows a histogram for a bright image, and
a and 4c show histograms for medium-bright images, and
Reference will now be made in detail to a particular embodiment of the invention examples of which are illustrated in the accompanying drawings. While the invention will be described in conjunction with the particular embodiments, it will be understood that it is not intended to limit the invention to the described embodiments. To the contrary, it is intended to cover alternatives, modifications, and equivalents as may be included within the spirit and scope of the invention as defined by the appended claims.
When a digital display device, such as a liquid crystal display (LCD) based display or a cathode-ray tube (CRT) based display, receives an input image, it is desirable to enhance the contrast of the input image before the image is displayed for viewing. Adaptive contrast enhancement refers to a general approach of analyzing the luminance spectrum of an input image and increasing or decreasing luminance in specific luminance ranges in order to enhance output image contrast. To accomplish this, first a luminance histogram is constructed for the input image by counting the number of pixels corresponding to luminance levels ranging over the input luminance range (the luminance spectrum). Then, output luminance levels are assigned according to a transfer curve, wherein a transfer curve is a mapping between input luminance levels and output luminance levels.
One approach to adaptive contrast enhancement comprises generating transfer curves that increase luminance in those image pixels that correspond to the most populated bins in the image histogram. Using this approach, bright pixels are brightened in mostly bright images, and dark pixels are brightened in mostly dark images.
A novel approach to adaptive contrast enhancement is disclosed herein. The fundamental idea is to generate transfer curves that brighten the bright pixels in mostly dark images, and darken the dark pixels in mostly bright images. This approach takes advantage of the fact that the least populated bins in the image histogram represent small image regions which are generally scattered and statistically distributed over the entire image area, as well as the fact that the human eye is not disturbed by small luminance adjustments to such regions. Advantages of this invention include greatly improved image contrast, clearer appearance of images to the eye, reduced cost of noise and contouring artifacts incurred as a result of using transfer functions, and a strong reduction in non-uniform brightness changes during fade-ins and fade-outs in video streams.
a shows an example medium-bright image and a histogram for the image.
In the following description, three luminance ranges are used to classify images: low-luminance, medium-luminance and high-luminance.
In accordance with one embodiment of the present invention, a histogram for a dark image is shown in
By way of example,
In accordance with another embodiment of the present invention, a histogram for a bright image is shown in
By way of example, a bright image may depict a scene of a sporting event on ice (such as a hockey game) having players wearing uniforms with dark details. In such an image, details in the dark areas of the picture (e.g. the texture of the uniforms) are not as relevant to a viewer as is following the action of the game and the movement of the black puck. For such a bright image, a transfer function such as the one shown in
For a medium-bright image, the technique is to increase the luminance in the high-luminance range and decrease the luminance in the low-luminance range of the image without substantially changing the luminance in the medium-luminance range of the image. Note that medium-bright images encompass a wide variety of luminance distributions, as shown in the example histograms of
b is a transfer curve for enhancing the contrast of an image having a histogram as shown in
d is a transfer curve for enhancing the contrast of an image having a histogram as shown in
One advantageous aspect of the present invention is the greatly improved image contrast. While the average brightness of the output image may be slightly lower, output images appear clearer to the eye. Focusing on bright pixels in mostly dark images when increasing luminance allows for over-compensation of the bright pixels. While this may lead to a small loss of detail, confined to a relatively small image area represented by the small number of bright pixels, the result is an image with improved contrast. In most applications, and especially in moving images (such as a video stream), the loss of such detail is not noticeable to the eye and therefore can be traded off for improved image contrast. Similarly, a decrease in the luminance levels of darker pixels in a mostly bright image may lead to a small loss of detail, confined to the small area represented by the dark pixels, but the suppression of such dark pixels results in improved image contrast.
Another advantageous aspect of the present invention is the small cost of noise and contouring artifacts that are incurred as a result of using the above described transfer functions. While the techniques may result in some noise amplification and contouring artifacts, such side-effects are kept small due to the fact that the technique does not substantially alter the luminance of the most significantly represented pixel groups, i.e. the luminance of dark pixels in mostly dark images and the luminance of bright pixels in mostly bright images.
Another advantageous aspect of the present invention is a strong reduction in non-uniform brightness changes during fade-ins and fade-outs in video streams. This also is due to the fact that the technique does not substantially alter the luminance levels of dark pixels in mostly dark images and the luminance levels of bright pixels in mostly bright images.
For smooth contrast enhancement in a sequence of images (such as in a video stream), the transfer functions can be applied adaptively based on the image content of the most recent frames. One implementation of this technique comprises accumulating the histograms of the most recent set of frames and computing their average. Based on the resulting average histogram, an appropriate transfer function is chosen for contrast enhancement. When implementing such an averaging technique, a buffer of 5 to 15 frames has been found to work well.
The invention has been described in the context of displaying an image on a digital display device. It should be appreciated that the same techniques can be used to limit the adaptive contrast enhancement to a region in the display. By way of example, adaptive contrast enhancement for a movie may exclude the upper and lower black bands that run horizontally across the display. By way of another example, adaptive contrast enhancement may be restricted to a user-definable region of the display, such as a window or a physical region of the display.
Foregoing described embodiments of the invention are provided as illustrations and descriptions. They are not intended to limit the invention to precise form described. Other variations and embodiments are possible in light of above teachings, and it is thus intended that the scope of invention not be limited by this Detailed Description, but rather by Claims following.
This application claims priority of U.S. provisional application No. 60/619,202 filed on Oct. 15, 2004 which is hereby incorporated by reference.
Number | Name | Date | Kind |
---|---|---|---|
5450502 | Eschbach et al. | Sep 1995 | A |
5828793 | Mann | Oct 1998 | A |
5949918 | McCaffrey | Sep 1999 | A |
6163621 | Paik et al. | Dec 2000 | A |
6239782 | Siegel | May 2001 | B1 |
6594388 | Gindele et al. | Jul 2003 | B1 |
6650664 | Moore et al. | Nov 2003 | B1 |
6738527 | Kuwata et al. | May 2004 | B2 |
6778183 | Nair | Aug 2004 | B1 |
7034843 | Nair et al. | Apr 2006 | B2 |
7050114 | Stessen et al. | May 2006 | B2 |
7127123 | Wredenhagen et al. | Oct 2006 | B2 |
7221807 | Campbel | May 2007 | B2 |
20020101432 | Ohara et al. | Aug 2002 | A1 |
20030161549 | Lei et al. | Aug 2003 | A1 |
20040008903 | Kim | Jan 2004 | A1 |
Number | Date | Country |
---|---|---|
0 648 040 | Apr 1995 | EP |
0648040 | Apr 1995 | EP |
0 366 099 | Jan 1996 | EP |
0 772 158 | May 1997 | EP |
1 418 543 | May 2004 | EP |
Number | Date | Country | |
---|---|---|---|
20060082689 A1 | Apr 2006 | US |
Number | Date | Country | |
---|---|---|---|
60619202 | Oct 2004 | US |