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1. (WO2019046221) LOCAL TONE MAPPING
Примечание: Текст, основанный на автоматизированных процессах оптического распознавания знаков. Для юридических целей просьба использовать вариант в формате PDF

What is claimed is:

1. A system comprising:

an image sensor configured to capture an image; and

a processing apparatus configured to:

receive the image from the image sensor;

apply a bilateral filter to the image to obtain a low-frequency component image and a high-frequency component image;

determine a first enhanced image based on a weighted sum of the low-frequency component image and the high-frequency component image, where the high-frequency component image is weighted more than the low-frequency component image;

determine a second enhanced image based on the first enhanced image and a tone mapping;

determine a perceptual domain image based on the second enhanced image and a gamma curve that models human perception of contrast;

determine a low-frequency component perceptual domain image and a high- frequency component perceptual domain image as components of the perceptual domain image;

determine a third enhanced image based on a weighted sum of the low- frequency component perceptual domain image and the high-frequency component perceptual domain image, where the high-frequency component perceptual domain image is weighted more than the low-frequency component perceptual domain image; and

store, display, or transmit an output image based on the third enhanced image.

2. The system of claim 1, in which determining the second enhanced image based on the first enhanced image and the tone mapping comprises:

applying the tone mapping to the low-frequency component image to obtain gains for respective image portions; and

applying the gains for respective image portions to corresponding image portions of the first enhanced image.

3. The system of any of claims 1 to 2, in which the processing apparatus is configured to:

determine the tone mapping based on a histogram analysis of image portions of the of the low-frequency component image.

4. The system of any of claims 1 to 3, in which determining the low-frequency component perceptual domain image comprises applying a transformation, based on the gamma curve, to a result of applying the tone mapping to the low-frequency component image.

5. The system of any of claims 1 to 4, in which determining the output image comprises: determining gains for respective image portions based on the third enhanced image and the gamma curve; and

applying the gains for respective image portions to corresponding image portions of the image.

6. The system of any of claims 1 to 5, in which the processing apparatus is configured to:

determine a reduced resolution image based on the image that is at a lower resolution than the image; and

in which applying the bilateral filter comprises processing pixels of the reduced resolution image as candidates.

7. The system of any of claims 1 to 6, in which applying the bilateral filter comprises: subsampling candidates within a range of distances from a kernel center.

8. The system of any of claims 1 to 6, in which applying the bilateral filter comprises: subsampling candidates at a first subsampling factor within a first range of distances from a kernel center; and

subsampling candidates at a second subsampling factor within a second range of distances from the kernel center.

9. The system of any of claims 1 to 8, in which determining the first enhanced image comprises:

checking an underflow condition for an image portion of the first enhanced image; and

where the underflow condition occurs, adding an offset to a corresponding image portion of the low-frequency component image, and subtracting the offset from a

corresponding image portion of the high-frequency component image.

10. The system of any of claims 1 to 9, in which the image sensor is attached to the processing apparatus.

11. A method comprising:

receiving an image from an image sensor;

applying a filter to the image to obtain a low-frequency component image and a high-frequency component image;

determining a first enhanced image based on a weighted sum of the low-frequency component image and the high-frequency component image, where the high-frequency component image is weighted more than the low-frequency component image;

determining a second enhanced image based on the first enhanced image and a tone mapping; and

storing, displaying, or transmitting an output image based on the second enhanced image.

12. The method of claim 11, in which determining the second enhanced image based on the first enhanced image and a tone mapping comprises:

applying the tone mapping to the low-frequency component image to obtain gains for respective image portions; and

applying the gains for respective image portions to corresponding image portions of the first enhanced image.

13. The method of any of claims 11 to 12, comprising:

determining a perceptual domain image based on the second enhanced image and a gamma curve that models human perception of contrast;

determining a low-frequency component perceptual domain image and a high-frequency component perceptual domain image as components of the perceptual domain image;

determining a third enhanced image based on a weighted sum of the low-frequency component perceptual domain image and the high-frequency component perceptual domain image, where the high-frequency component perceptual domain image is weighted more than the low-frequency component perceptual domain image; and

wherein the output image is based on the third enhanced image.

14. The method of claim 13, in which determining the low-frequency component perceptual domain image comprises applying a transformation, based on the gamma curve, to a result of applying the tone mapping to the low-frequency component image.

15. The method of any of claims 13 to 14, in which determining the output image comprises:

determining gains for respective image portions based on the third enhanced image and the gamma curve; and

applying the gains for respective image portions to corresponding image portions of the image.

16. A system compri sing :

an image sensor configured to capture an image; and

a processing apparatus configured to:

receive the image from the image sensor;

apply a filter to the image to obtain a low-frequency component image and a high-frequency component image;

apply a non-linear mapping to the low-frequency component image to obtain gains for respective image portions;

apply the gains for respective image portions to corresponding image portions of the image to obtain an enhanced image; and

store, display, or transmit an output image based on the enhanced image.

17. The system of claim 16, in which the processing apparatus is configured to:

determine the non-linear mapping based on a histogram analysis of image portions of the of the low-frequency component image.

18. The system of any of claims 16 to 17, in which the processing apparatus is configured to:

determine a perceptual domain image based on the enhanced image and a gamma curve that models human perception of contrast;

determine a low-frequency component perceptual domain image and a high-frequency component perceptual domain image as components of the perceptual domain image;

determine an enhanced perceptual domain image based on a weighted sum of the low-frequency component perceptual domain image and the high-frequency component perceptual domain image, where the high-frequency component perceptual domain image is weighted more than the low-frequency component perceptual domain image; and

wherein the output image is based on the enhanced perceptual domain image.

19. The system of claim 18, in which determining the low-frequency component perceptual domain image comprises applying a transformation, based on the gamma curve, to a result of applying the gains for respective image portions to the low-frequency component image.

20. The system of any of claims 18 to 19, in which determining the output image comprises:

determining gains for respective image portions based on the enhanced perceptual domain image and the gamma curve; and

applying the gains for respective image portions to corresponding image portions of the image.