Sample Adaptive Offset for Video Encoding Artifact Reduction
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Solution Overview
Problem
Image encoding techniques using prediction methods result in variations between source and decoded image data, leading to perceivable visual artifacts such as blocking, banding, and ringing in displayed image frames.
Innovation Solution
A video encoding pipeline determines sample adaptive offset parameters to adjust decoded image data, using deblock filtering and adaptive offset techniques to reduce these artifacts, by analyzing reconstructed and deblocked image data and selecting optimal offset samples to apply band and edge offsets based on rate-distortion costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If prediction techniques are used to encode source image data, then transmission bandwidth and memory usage are reduced, but visual artifacts such as blocking, banding, and ringing appear in displayed image frames
Solution Approach 1:
The patent introduces an intermediary processing stage between decoding and display. Sample adaptive offset values are calculated based on neighboring reconstructed samples and applied to adjust the decoded image data before display. This intermediary adjustment reduces visual artifacts while maintaining the compression benefits of prediction techniques.
Solution Approach 2:
The patent changes parameters of the decoded image data by applying sample adaptive offset values. These offsets are calculated based on local characteristics of neighboring reconstructed samples, allowing dynamic parameter adjustment to reduce artifacts in different regions of the image while maintaining overall compression efficiency.
2Object-affected harmful factors
If deblock filtering parameters are applied to reduce blocking artifacts, then visual quality improves, but computational complexity increases
Solution Approach 1:
The patent applies deblock filtering selectively based on local image characteristics. Boundary strength parameters are determined by analyzing local variations in reconstructed samples, allowing stronger filtering where blocking artifacts are more likely and weaker filtering where they are less likely. This local adaptation reduces overall computational complexity while maintaining visual quality.
3Object-affected harmful factors
If sample adaptive offset parameters are dynamically adjusted to reduce artifacts, then image quality improves, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary calculations of sample adaptive offset values using neighboring reconstructed samples that are already available during the decoding process. By preparing these offset values in advance based on locally available data, the method reduces artifacts without requiring additional processing time after the main decoding is complete.
Data Source
AI summary
Systems and methods for improving operation of a video encoding pipeline, which includes a sample adaptive offset block that selects an offset sample from image data corresponding with a coding unit; determines edge offset parameters including a first mapping of an edge classification to an edge offset value and band offset parameters including a second mapping of a band classification to a band offset value based at least in part on analysis of the offset sample; and determines sample adaptive offset parameters based at least in part on a first rate-distortion cost associated with the edge offset parameters and a second rate-distortion cost associated with the band offset parameters. Additionally, a decoding device may apply offsets to decoded image data corresponding with the coding unit based at least in part on the sample adaptive offset parameters.