IP Library › Granted Patent US 11,847,808
Granted Patent B2
US 11,847,808 · App. 17/030,113 · Granted Dec 19, 2023

Systems and methods region-of-interest automatic gain or exposure control

Inventors: Edwin Chongwoo Park (San Diego, CA); Soman Ganesh Nikhara (Hyderabad, IN); Bapineedu Chowdary Gummadi (Hyderabad, IN); Pradeep Veeramalla (Hyderabad, IN); Ravi Shankar Kadambala (Hyderabad, IN)
Assignee: QUALCOMM Incorporated
G06V10/25G06F17/18H04N23/71H04N23/73
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Quick Facts
Patent No.
US 11,847,808
App. No.
17/030,113
Granted
Dec 19, 2023
Kind
B2
Abstract

Methods, systems, computer-readable media, and apparatuses for region-of-interest automatic gain or exposure control are presented. One example method includes receiving an image from an image sensor, the image comprising a plurality of pixels, determining a region of interest (“ROI”) in the image, the ROI comprising a subset of the plurality of pixels in the image, determining a ROI weight for pixels in the subset of the plurality of pixels, determining statistics for the image based on the plurality of pixels in the image and the ROI weight, and adjusting a gain or exposure setting for the image sensor based on the statistics.

Claims (76)

1. A method comprising:

receiving a first image from an image sensor, the first image comprising a first plurality of pixels;

receiving a second image from the image sensor, the second image comprising a second plurality of pixels;

determining a region of interest (ROI) in the second image, the ROI in the second image comprising a subset of the second plurality of pixels in the second image;

determining an ROI weight for the ROI in the second image;

determining statistics based on the first plurality of pixels in the first image, the subset of the second plurality of pixels in the second image, and the ROI weight for the ROI in the second image; and

adjusting a gain or exposure setting for the image sensor based on the statistics.

2. The method of claim 1 comprising receiving a third image from the image sensor, the third image based on the gain or exposure setting.

3. The method of claim 1 , further comprising:

applying first weights to the first plurality of pixels; and

wherein the ROI weight for the ROI in the second image comprises a combination of the first weights applied to the first plurality of pixels and an ROI value.

4. The method of claim 3 , wherein determining the statistics comprises combining (a) weighted pixel values for the first plurality of pixels in the first image based on the first weights and (b) weighted pixel values for the subset of the second plurality of pixels in the second image based on the ROI weight.

5. The method of claim 4 , wherein the first image is received before the second image.

6. The method of claim 1 , wherein the subset of the second plurality of pixels is a first subset of the second plurality of pixels in the second image, the method further comprising:

determining a second ROI in the second image, the second ROI comprising a second subset of the second plurality of pixels in the second image; and

determining a second ROI weight of pixels in the second subset of the second plurality of pixels; and

wherein determining the statistics is further based on the second subset of the second plurality of pixels and the second ROI weight.

7. The method of claim 1 , wherein determining the statistics comprises determining one of an average brightness value, a total brightness value, or a total squared brightness value.

8. The method of claim 1 , further comprising receiving a user input identifying an object in the second image to define the ROI.

9. A device comprising:

a non-transitory computer-readable medium; and

a processor communicatively coupled to the non-transitory computer-readable medium, the processor configured to:

receive a first image from an image sensor, the first image comprising a first plurality of pixels;

receive a second image from the image sensor, the second image comprising a second plurality of pixels;

determine a region of interest (ROI) in the second image, the ROI in the second image comprising a subset of the second plurality of pixels in the second image;

determine an ROI weight for the ROI in the second image;

determine statistics based on the first plurality of pixels in the first image, the subset of the second plurality of pixels in the second image, and the ROI weight for the ROI in the second image; and

adjust a gain or exposure setting for the image sensor based on the statistics.

10. The device of claim 9 , further comprising the image sensor.

11. The device of claim 9 , wherein the processor is further configured to receive a third image from the image sensor, the third image based on the gain or exposure setting.

12. The device of claim 9 , wherein the processor is further configured to:

apply first weights to the first plurality of pixels; and

wherein the ROI weight for the ROI in the second image comprises a combination of the first weights applied to the first plurality of pixels and an ROI value.

13. The device of claim 12 , wherein the processor is configured to determine the statistics by combining (a) weighted pixel values for the first plurality of pixels in the first image based on the first weights and (b) weighted pixel values for the subset of the second plurality of pixels in the second image based on the ROI weight.

14. The device of claim 13 , wherein the processor is configured to receive the first image before the second image.

15. The device of claim 9 , wherein the subset of the second plurality of pixels is a first subset of the second plurality of pixels in the second image, and the processor is further configured to:

determine a second ROI in the second image, the second ROI comprising a second subset of the second plurality of pixels in the second image; and

determine a second ROI weight of pixels in the second subset of the second plurality of pixels; and

wherein the processor is further configured to determine the statistics further based on the second subset of the second plurality of pixels and the second ROI weight.

16. The device of claim 9 , wherein the processor is further configured to determine the statistics by determining one of an average brightness value, a total brightness value, or a total squared brightness value.

17. A non-transitory computer-readable medium comprising processor-executable instructions configured to cause a processor to:

receive a first image from an image sensor, the first image comprising a first plurality of pixels;

receive a second image from the image sensor, the second image comprising a second plurality of pixels;

determine a region of interest (ROI) in the second image, the ROI in the second image comprising a subset of the second plurality of pixels in the second image;

determine an ROI weight for the ROI in the second image;

determine statistics based on the first plurality of pixels in the first image, the subset of the second plurality of pixels in the second image, and the ROI weight for the ROI in the second image; and

adjust a gain or exposure setting for the image sensor based on the statistics.

18. The non-transitory computer-readable medium of claim 17 , further comprising processor-executable instructions configured to cause the processor to receive a third image from the image sensor, the third image based on the gain or exposure setting.

19. The non-transitory computer-readable medium of claim 17 , further comprising processor-executable instructions configured to cause the processor to:

apply first weights to the first plurality of pixels; and

wherein the ROI weight for the ROI in the second image comprises a combination of the first weights applied to the first plurality of pixels and an ROI value.

20. The non-transitory computer-readable medium of claim 19 , further comprising processor-executable instructions configured to cause the processor to determine the statistics by combining (a) weighted pixel values for the first plurality of pixels in the first image based on the first weights and (b) weighted pixel values for the subset of the second plurality of pixels in the second image based on the ROI weight.

21. The non-transitory computer-readable medium of claim 20 , wherein the processor-executable instructions are configured to cause the processor to receive the first image before the second image.

22. The non-transitory computer-readable medium of claim 17 , wherein the subset of the second plurality of pixels is a first subset of the second plurality of pixels in the second image, the non-transitory computer-readable medium further comprising processor-executable instructions configured to cause the processor to:

determine a second ROI in the second image, the second ROI comprising a second subset of the second plurality of pixels in the second image; and

determine a second ROI weight of pixels in the second subset of the second plurality of pixels; and

wherein the processor-executable instructions are configured to cause the processor to determine the statistics further based on the second ROI weight.

23. The non-transitory computer-readable medium of claim 17 , further comprising processor-executable instructions configured to cause the processor to determine the statistics by determining one of an average brightness value, a total brightness value, or a total squared brightness value.

24. An apparatus comprising:

means for receiving a first image from an image sensor, the first image comprising a first plurality of pixels;

means for receiving a second image from the image sensor, the second image comprising a second plurality of pixels;

means for determining a region of interest (ROI) in the second image, the ROI in the second image comprising a subset of the second plurality of pixels in the second image;

means for determining an ROI weight for the ROI in the second image;

means determining statistics based on the first plurality of pixels in the first image, the subset of the second plurality of pixels in the second image, and the ROI weight for the ROI in the second image; and

means for adjusting a gain or exposure setting for the image sensor based on the statistics.

25. The apparatus of claim 24 , further comprising means for capturing the first image and the second image.

26. The apparatus of claim 24 , further comprising:

means for applying first weights to the first plurality of pixels; and

wherein the ROI weight for the ROI in the second image comprises a combination of the first weights applied to the first plurality of pixels and an ROI value.

27. The apparatus of claim 26 , wherein the means for determining the statistics comprises means for combining (a) weighted pixel values for the first plurality of pixels in the first image based on the first weights and (b) weighted pixel values for the subset of the second plurality of pixels in the second image based on the ROI weight.

28. The apparatus of claim 27 , wherein the means for receiving the first image comprises means for receiving the first image before the second image.

29. The apparatus of claim 24 , wherein the subset of the second plurality of pixels is a first subset of the second plurality of pixels in the second image, the apparatus further comprising:

means for determining a second ROI in the second image, the second ROI comprising a second subset of the second plurality of pixels in the second image; and

means for determining a second ROI weight of pixels in the second subset of the second plurality of pixels; and

wherein the means for determining the statistics comprises means for determining the statistics further based on the second ROI weight.

30. The apparatus of claim 24 , wherein the means for determining the statistics comprises means for determining one of an average brightness value, a total brightness value, or a total squared brightness value.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 17, 2021
From: PARK, EDWIN CHONGWOO; NIKHARA, SOMAN GANESH; GUMMADI, BAPINEEDU CHOWDARY; VEERAMALLA, PRADEEP; KADAMBALA, RAVI SHANKAR
To: QUALCOMM INCORPORATED
Reel/Frame 055300/0678 →
Continuity (2)
Provisional Application 62914600 · Oct 14, 2019
Related Publication 20210110190A1 · Apr 15, 2021
Cited By (3)
US 12,217,471 US 12,407,913 US 12,659,571