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 contrast enhancement system, comprising:
a histogram updater that is configured to provide a current-frame cumulative histogram based on a received image frame, to divide the current-frame histogram into regions, to determine an arithmetic mean for at least two of the regions of the current-frame histogram, and to calculate variances for each of the determined arithmetic means;
a weighting factor calculator that is configured to calculate weighting factors based on the calculated variances; and
an equalizer that is configured to transform pixel values of the received image frame using the weighting factors and statistics from a previous-frame cumulative histogram.
2. The system of claim 1 , wherein the histogram updater is configured to determine the arithmetic means in accordance with the equation
m
i
=
∑
j
y
j
N
where y j represents luma of points in a particular region i and N is the total number of points in that region.
3. The system of claim 2 , wherein the histogram updater is configured to calculate the variances in accordance with the equation
σ
i
=
1
N
∑
j
n
(
y
j
)
(
y
j
-
m
i
)
where n(y j ) is a count of the number of pixels of luma y j and σ i is the variance of the ith region.
4. The system of claim 1 , wherein the equalizer is configured to transform pixels of the received video frame using the equation of claim 3 .
5. The system of claim 1 , wherein the current-frame cumulative histogram and the previous-frame cumulative histogram are stored in two memories, on an alternating basis, in response to receiving the received image frame.
6. The system of claim 5 , wherein a cumulative density function result set for a current frame is stored in a first memory for the current-frame cumulative histogram, and a cumulative density function result set for a previous frame is stored in a second memory for the previous-frame cumulative histogram.
7. The system of claim 5 , wherein a cumulative density function result set for a current frame is stored in a first memory for the current-frame cumulative histogram, and a cumulative density function result set for a previous frame is applied to a previous frame that is being output from the second memory.
8. The system of claim 1 , wherein the statistics from the previous-frame cumulative histogram include a reciprocal of a number of points in each region.
9. The system of claim 3 , wherein the weighting factor calculator is configured to calculate the weighting factors in accordance with a weighting factor curve that defines a weighting factor for each calculated variance.
10. The system of claim 9 , wherein each region has a respective weighting factor curve that depends on a desired level of enhancement.
11. A method for enhancing contrast of an image, comprising:
generating a current-frame cumulative histogram based on a received image frame;
dividing the current-frame histogram into regions;
determining an arithmetic mean for at least two of the regions of the current-frame histogram;
calculating variances for each of the determined arithmetic means;
calculating weighting factors based on the calculated variances; and
transforming pixel values of the received image frame using the weighting factors and statistics from a previous-frame cumulative histogram.
12. The method of claim 11 , wherein the arithmetic means are determined in accordance with the equation
m
i
=
∑
j
y
j
N
,
where y j represents luma of points in a particular region i and N is the total number of points in that region.
13. The method of claim 12 , wherein the variances are calculated in accordance with the equation
σ
i
=
1
N
∑
j
n
(
y
j
)
(
y
j
-
m
i
)
,
where n(y j ) is a count of the number of pixels of luma y j and σ i is the variance of the ith region.
14. The method of claim 11 , wherein the pixels of the received video frame are transformed using the equation of claim 13 .
15. The method of claim 11 further comprising storing the current-frame cumulative histogram and the previous-frame cumulative histogram in two memories, on an alternating basis.
16. The method of claim 15 further comprising storing a cumulative density function result set for a current frame in a first memory for the current-frame cumulative histogram, and a cumulative density function result set for a previous frame in a second memory for the previous-frame cumulative histogram.
17. The method of claim 15 further comprising:
storing a cumulative density function result set for a current frame in a first memory for the current-frame cumulative histogram; and
applying a cumulative density function result set for a previous frame to a previous frame that is being output from the second memory.
18. The method of claim 11 , wherein the statistics from the previous-frame cumulative histogram include a reciprocal of a number of points in each region.
19. The method of claim 18 further comprising calculating the weighting factors in accordance with a weighting factor curve that defines a weighting factor for each calculated variance.
20. The method of claim 19 , wherein each region has a respective weighting factor curve that depends on a desired level of enhancement.