Adaptive histogram-based video contrast enhancement
View Patent ↗The adaptive contrast enhancer uses an adaptive histogram equalization-based approach to improve contrast in a video signal. For each video frame, the histogram of the pixel luminance values is calculated. The calculated histogram is divided into three regions that are equalized independently of the other. The equalized values are averaged with the original pixel values with a weighting factor that depends on the shape of the histogram. The weighting factors can be also chosen differently for the three regions to enhance the darker regions more than the brighter ones. The statistics calculated from one frame are used to enhance the next frame such that frame buffers are not required. Many of the calculations are done in the inactive time between two frames.
1. A method for processing a video signal, comprising:
deriving a histogram of a received signal of an image using a histogram updater, wherein the histogram comprises pixel luminance information associated with pixels in the image, and wherein the histogram defines a range of luminance values;
processing the histogram with an equalizer by:
dividing the histogram into regions corresponding to pre-determined sub-ranges of the defined range of luminance values, wherein each region comprises a portion of the pixel luminance information; and
equalizing each region to provide equalized pixel luminance values, wherein a given region is equalized based on a cumulative density function that calculates a probability of a pixel in the given region having a luminance value equal to or less than a given luminance value;
calculating a mean luminance value for each region, wherein the mean luminance value of each respective region depends only on the portion of the pixel luminance information associated with that region;
calculating a weighting factor for each region based on the mean luminance value of that region using a weighting factor calculator; and
providing output pixel luminance values, with the equalizer, based on a weighted average of the pixel luminance information and the equalized pixel luminance values in accordance with each of the weighting factors.
2. The method of claim 1 , wherein the weighting factor of a first region differs from the weighting factor of a second region.
3. The method of claim 1 , wherein the weighting factor is calculated for each region in accordance with a shape of the histogram.
4. The method of claim 1 , wherein the weighting factor is calculated for each region based on a weighting factor curve that relates histogram variance values to weighting factor values.
5. The method of claim 1 , wherein the cumulative density function is determined separately for each region.
6. The method of claim 1 , wherein the weighting factor is calculated for each region in accordance with the equation:
σ
i
=
1
N
∑
j
n
(
y
j
)
(
y
j
-
m
i
)
,
where
m
i
=
∑
j
y
j
N
,
where y j represents luma of points in a region i, N is a total number of points in the region i, n(y j ) is a count of a number of pixels of luma y j , and σ i is a variance of the region i.
7. The method of claim 1 , wherein the method is performed in a period of time that is around a blanking interval between two successive image frames in the received signal.
8. The method of claim 1 , wherein the method is performed on a real-time basis.
9. A contrast enhancement system, comprising:
means for deriving a histogram of a received signal of an image, wherein the histogram comprises pixel luminance information associated with pixels in the image, and wherein the histogram defines a range of luminance values;
means for dividing the histogram into regions corresponding to pre-determined sub-ranges of the defined range of luminance values, wherein each region comprises a portion of the pixel luminance information;
means for equalizing each region to provide equalized pixel luminance values, wherein a given region is equalized based on a cumulative density function that calculates a probability of a pixel in the given region having a luminance value equal to or less than a given luminance value;
means for calculating a mean luminance value for each region, wherein the mean luminance value of each respective region depends only on the portion of the pixel luminance information associated with that region;
means for calculating a weighting factor for each region based on the mean luminance value of that region; and
means for providing output pixel luminance values based on a weighted average of the pixel luminance information and the equalized pixel luminance values in accordance with each of the weighting factors.
10. The system of claim 9 , wherein the weighting factor of a first region differs from the weighting factor of a second region.
11. The system of claim 9 , wherein the means for calculating the weighting factor for each region calculates the weighting factor for each region in accordance with a shape of the histogram.
12. The system of claim 9 , wherein the means for equalizing each region comprises means for determining the cumulative density function separately for each region.
13. The system of claim 9 , wherein the means for equalizing each region equalizes each region in a period of time that is around a blanking interval between two successive image frames in the received signal.
14. The method of claim 1 , wherein each of the pre-determined sub-ranges contains a substantially equal number of luminance values.
15. The method of claim 4 , wherein each region is associated with its own weighting factor curve, and wherein the weighting factor of each respective region is calculated based on the weighting factor curve of that region.
16. The system of claim 9 , wherein each of the pre-determined sub-ranges contains a substantially equal number of luminance values.
17. The system of claim 9 , wherein the means for calculating the weighting factor for each region calculates the weighting factor for each region based on a weighting factor curve that relates histogram variance values to weighting factor values.
18. The system of claim 17 , wherein each region is associated with its own weighting factor curve, and wherein the means for calculating the weighting factor for each region calculates the weighting factor of each respective region based on the weighting factor curve of that region.