Pixel processing
View Patent ↗A method of processing pixels of an image comprises determining the most homogenous region of the image, calculating a threshold (th) according to the content of the determined region, selecting pixels in the image according to the calculated threshold (th), and applying a gain to the selected pixels. The method can also further comprise calculating the gain according to the content of the image.
1. A method of processing pixels of an image comprising:
segmenting the image into smaller segments according to a predetermined algorithm;
determining a variance of pixels in the respective segments;
determining a homogeneity value from the variance of the pixels in the respective segments;
determining a most homogenous region of the pixel image from the homogeneity value;
calculating a first normalized accumulated histogram of the edge transitions within the most homogenous region;
calculating a threshold value based on the first histogram;
calculating a second normalized accumulated histogram of the edge transitions that are above the threshold value;
calculating a gain of the image peaking from the second histogram;
using the threshold value to select those pixels to which image peaking is to be applied; and
applying the gain to the selected image pixels.
2. The method according to claim 1 , wherein the calculating a gain comprises calculating the gain for a specific pixel be equal to the maximum grey level of the image multiplied by the computed value multiplied by an output of a filter of the specific pixel.
3. A system of processing pixels of an image comprising:
a receiver arranged to receive an image; and
a processor arranged to
segment the image into smaller segments according to a predetermined algorithm;
determine a variance of pixels in the respective segments;
determine a homogeneity value from the variance of the pixels in the respective segments;
determining a most homogenous region of the pixel image from the homogeneity value;
calculate a first normalized accumulated histogram of the edge transitions within the most homogenous region;
calculate a threshold value based on the first histogram;
calculate a second normalized accumulated histogram of the edge transitions that are above the threshold value;
calculate a gain of the image peaking from the second histogram;
use the threshold value to select those pixels to which image peaking is to be applied; and
apply the gain to the selected image pixels.
4. The system according to claim 3 , wherein the processor is arranged, when calculating a gain, to calculate the gain for a specific pixel to be equal to the maximum grey level of the image multiplied by the computed value multiplied by an output of a filter of the specific pixel.
5. A non-transitory computer readable medium encoded with data and instructions to process pixels of an image, that when executed by a computer, causes the computer to:
segment the image into smaller segments according to a predetermined algorithm;
determine a variance of pixels in the respective segments;
determine a homogeneity value from the variance of the pixels in the respective segments;
determine a most homogenous region of the pixel image from the homogeneity value;
calculate a first normalized accumulated histogram of the edge transitions within the most homogenous region;
calculate a threshold value based on the first histogram;
calculate a second normalized accumulated histogram of the edge transitions that are above the threshold value;
calculate a gain of the image peaking from the second histogram;
use the threshold value to select those pixels to which image peaking is to be applied; and
apply the gain to the selected image pixels.
6. The non-transitory computer-readable medium according to claim 5 , wherein the calculating of a gain comprises instructions for calculating the gain for a specific pixel to be equal to the maximum grey level of the image multiplied by the computed value multiplied by an output of a filter of the specific pixel.
7. The method of claim 1 , said predetermined algorithm comprising:
computing the edges between pixels; and
ordering the computed edges from low to high.
8. The method of claim 7 , wherein each of said computed edges is identified by an identifier and a value.
9. The method of claim 1 , wherein the threshold value is calculated for the whole image and not for any individualized region within the image.
10. The method of claim 1 , wherein the method is performed on every nth image in a plurality of images, wherein n is an integer greater than one.
11. The system of claim 3 , said predetermined algorithm comprising:
computing the edges between pixels; and
ordering the computed edges from low to high.
12. The system of claim 11 , wherein each of said computed edges is identified by an identifier and a value.
13. The system of claim 3 , wherein the threshold value is calculated for the whole image and not for any individualized region within the image.
14. The non-transitory computer readable medium of claim 5 , the instructions further causing the computer to:
compute the edges between pixels; and
order the computed edges from low to high.
15. The non-transitory computer readable medium of claim 14 , wherein each of said computed edges is identified by an identifier and a value.
16. The non-transitory computer readable medium of claim 5 , wherein the threshold value is calculated for the whole image and not for any individualized region within the image.