Control of video encoding based on one or more video capture parameters

Patent metadata

Field	Value
Publication number	US-10178406-B2
Application number	US-77449110-A
Country	US
Kind code	B2
Filing date	May 5, 2010
Priority date	Nov 6, 2009
Publication date	Jan 8, 2019
Grant date	Jan 8, 2019

Abstract

This disclosure describes techniques for improving functionalities of a video encoder, using parameters detected and estimated by a front-end video capture device. The techniques may involve estimating a blurriness level associated with frames captured during a refocusing process. Based on the estimated blurriness level, the quantization parameter (QP) used to encode blurry frames is adjusted either in the video capture device or in the video encoder. The video encoder uses the adjusted QP to encode the blurry frames. The video encoder also uses the blurriness level estimate to adjust encoding algorithms by simplifying motion estimation and compensation in the blurry frames.

First claim

The invention claimed is:

1. A method comprising:
estimating, in a video capture module, a blurriness level of a frame of video data captured during a refocusing process, wherein said estimating is based on at least one refocusing statistic associated with the frame; and
encoding, in a video encoder, the frame based at least in part on the estimated blurriness level of the frame.

2. The method of claim 1 , wherein said at least one refocusing statistic includes at least one of (A) a focus value associated with the frame and (B) an indication of lens position.

3. The method of claim 1 , wherein encoding comprises selecting, based on the estimated blurriness level, a level of quantization to be used for encoding the frame.

4. The method of claim 3 , wherein selecting a level of quantization comprises:
selecting a first quantization level for a first estimated blurriness level; and
selecting a second quantization level for a second estimated blurriness level,
wherein the first quantization level is larger than the second quantization level and the first estimated blurriness level is larger than the second estimated blurriness level.

5. The method of claim 1 , wherein encoding comprises selecting, based on the estimated blurriness level, a partition size to be used for encoding the frame.

6. The method of claim 5 , wherein selecting a partition size comprises:
selecting a first partition for a first estimated blurriness level; and
selecting a second partition for a second estimated blurriness level,
wherein the first partition is larger than the second partition and the first estimated blurriness level is larger than the second estimated blurriness level.

7. The method of claim 1 , wherein encoding comprises selecting, based on the estimated blurriness level, a pixel precision level to be used for encoding the frame.

8. The method of claim 7 , wherein selecting a pixel precision level comprises:
selecting a first pixel precision level for a first estimated blurriness level; and
selecting a second pixel precision level for a second estimated blurriness level,
wherein the first pixel precision level is lower than the second pixel precision level and the first estimated blurriness level is larger than the second estimated blurriness level.

9. The method of claim 1 , wherein encoding comprises selecting, based on the estimated blurriness level, a set of reference frames to be used for encoding the frame.

10. The method of claim 9 , wherein selecting a set of reference frames comprises:
selecting a first set of reference frames for a first estimated blurriness level; and
selecting a second set of reference frames for a second estimated blurriness level,
wherein the first set of reference frames is smaller than the second set of reference frames and the first estimated blurriness level is larger than the second estimated blurriness level.

11. The method of claim 1 , wherein encoding comprises one of:
discarding the frame if the estimated blurriness level exceeds a threshold; and
encoding the frame using skip mode if the estimated blurriness level exceeds the threshold.

12. A system comprising:
a video capture module to estimate a blurriness level of a frame of video data captured during a refocusing process of the video capture module, wherein said estimating is based on at least one refocusing statistic associated with the frame; and
a video encoder to encode the frame based at least in part on the estimated blurriness level of the frame.

13. The system of claim 12 , wherein said at least one refocusing statistic includes at least one of (A) a focus value associated with the frame and (B) an indication of lens position.

14. The system of claim 12 , wherein the video encoder encodes the frame by selecting, based on the estimated blurriness level, a level of quantization to be used for encoding the frame.

15. The system of claim 14 , wherein the video encoder selects a level of quantization by:
selecting a first quantization level for a first estimated blurriness level; and
selecting a second quantization level for a second estimated blurriness level,
wherein the first quantization level is larger than the second quantization level and the first estimated blurriness level is larger than the second estimated blurriness level.

16. The system of claim 12 , wherein the video encoder encodes the frame by selecting, based on the estimated blurriness level, a partition size to be used for encoding the frame.

17. The system of claim 16 , wherein the video encoder selects a partition size by:
selecting a first partition for a first estimated blurriness level; and
selecting a second partition for a second estimated blurriness level,
wherein the first partition is larger than the second partition and the first estimated blurriness level is larger than the second estimated blurriness level.

18. The system of claim 12 , wherein the video encoder encodes the frame by selecting, based on the estimated blurriness level, a pixel precision level to be used for encoding the frame.

19. The system of claim 18 , wherein the video encoder selects a pixel precision level by:
selecting a first pixel precision level for a first estimated blurriness level; and
selecting a second pixel precision level for a second estimated blurriness level,
wherein the first pixel precision level is lower than the second pixel precision level and the first estimated blurriness level is larger than the second estimated blurriness level.

20. The system of claim 12 , wherein the video encoder encodes the frame by selecting, based on the estimated blurriness level, a set of reference frames to be used for encoding the frame.

21. The system of claim 20 , wherein the video encoder selects a set of reference frames by:
selecting a first set of reference frames for a first estimated blurriness level; and
selecting a second set of reference frames for a second estimated blurriness level,
wherein the first set of reference frames is smaller than the second set of reference frames and the first estimated blurriness level is larger than the second estimated blurriness level.

22. The system of claim 12 , wherein the video encoder encodes the frame by one of:
discarding the frame if the estimated blurriness level exceeds a threshold; and
encoding the frame using skip mode if the estimated blurriness level exceeds the threshold.

23. A non-transitory computer-readable medium comprising instructions for causing a programmable processor to:
estimate, in a video capture module, a blurriness level of a frame of video data captured during a refocusing process, wherein said estimating is based on at least one refocusing statistic associated with the frame; and
encode, in a video encoder, the frame based at least in part on the estimated blurriness level of the frame.

24. The non-transitory computer-readable medium of claim 23 , wherein said at least one refocusing statistic includes at least one of (A) a focus value associated with the frame and (B) an indication of lens position.

25. The non-transitory computer-readable medium of claim 23 , wherein the instructions to encode comprise instructions to select, based on the estimated blurriness level, a level of quantization to be used for encoding the frame.

26. The non-transitory computer-readable medium of claim 25 , wherein the instructions to select a level of quant

Assignees

• Liang Liang
• Hung Szepo R
• Qualcomm Inc

Inventors

• Liang Liang
• Hung Szepo R

Classifications

• H04N19/154

  Measured or subjectively estimated visual quality after decoding, e.g. measurement of distortion (use of rate-distortion criteria H04N19/147) · CPC title

• H04N19/179

  the unit being a scene or a shot · CPC title

• H04N19/132

  Sampling, masking or truncation of coding units, e.g. adaptive resampling, frame skipping, frame interpolation or high-frequency transform coefficient masking · CPC title

• H04N19/124

  Quantisation · CPC title

• H04N19/107

  between spatial and temporal predictive coding, e.g. picture refresh · CPC title