Bypass Arithmetic Coding for SAO Offset Values
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Solution Overview
Problem
Current image coding methods, particularly in the HEVC standard, face processing inefficiencies due to the requirement for context arithmetic coding in the SAO process, which involves loading and updating contexts, leading to sequential processing issues and reduced throughput.
Innovation Solution
Implementing bypass arithmetic coding on SAO offset values using a fixed probability, converting offset values into bin strings, and performing bypass arithmetic coding, which eliminates the need for context loading and updating, thereby accelerating the processing without compromising coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If context arithmetic coding is used in the SAO process, then coding efficiency is maintained, but processing speed decreases due to context loading and updating operations
Solution Approach 1:
The patent changes the parameter of arithmetic coding from context-based to bypass-based. By switching to bypass arithmetic coding with fixed probability (0.5) for encoding SAO offset values, the system eliminates context loading and updating operations, thereby significantly improving processing speed while maintaining acceptable coding efficiency through the use of fixed probability models that do not require adaptive parameter updates
2Productivity
If context arithmetic coding is used for SAO offset values, then coding accuracy is maintained, but processing throughput is reduced due to sequential operations
Solution Approach 1:
The patent extracts the context management component from the arithmetic coding process for SAO offset values. By removing the context loading and updating operations entirely and using bypass arithmetic coding instead, the system achieves higher throughput. The fixed probability model used in bypass coding provides sufficient accuracy for SAO offset values without requiring the sequential context adaptation operations
Data Source
AI summary
Image coding and decoding technologies are described. For example, a sample adaptive offset (SAO) type parameter is decoded from a bitstream, and an SAO type for an SAO value to be added to a pixel value of a reconstructed image is determined from the SAO type parameter. A plurality of bins with variable length coding is decoded from the bitstream using bypass arithmetic coding with a fixed probability. The plurality of bins represents an integer indicating a magnitude of the SAO value. The integer indicating the magnitude of the SAO value is determined based on the plurality of bins decoded using bypass arithmetic coding with a fixed probability. The SAO value is determined using the determined integer.