SAO Syntax Coding Layout for Parallel Video Decoding
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Solution Overview
Problem
Existing moving picture coding and decoding methods using Sample Adaptive Offset (SAO) in HEVC are inefficient in processing due to insufficient parallel processing capability and redundant bit lengths, leading to increased burden in coding and decoding.
Innovation Solution
Implement context adaptive binary arithmetic coding for first SAO information and bypass arithmetic coding for second and third SAO information, with the latter being placed after the former in the bit stream, allowing for continuous parallel processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If context adaptive binary arithmetic coding is used for all SAO information, then coding efficiency is improved, but processing speed deteriorates due to sequential processing requirements
Solution Approach 1:
The patent segments SAO information into two categories: first SAO information (sao_type_idx, sao_band_position) processed by context adaptive binary arithmetic coding for high compression efficiency, and second SAO information (sao_offset) processed by bypass arithmetic coding for fast parallel processing. This segmentation allows different processing strategies to be applied to different parts of the data, resolving the contradiction between compression efficiency and processing speed.
Solution Approach 2:
Different coding methods are applied to different parts of the SAO information based on their local characteristics. The first SAO information (category indices and position data) uses context adaptive coding matched to its statistical properties, while the second SAO information (offset values) uses bypass coding optimized for speed. This local optimization resolves the contradiction by matching processing method to data characteristics.
2Device complexity
If traditional SAO coding methods are used, then processing simplicity is maintained, but parallel processing capability is insufficient leading to increased processing burden
Solution Approach 1:
The patent divides the SAO coding process into two distinct segments with different processing methods. The first segment (category and position coding) maintains traditional sequential processing for simplicity, while the second segment (offset coding) implements parallel-friendly bypass arithmetic coding. This segmentation enables parallel processing capability to be introduced without complicating the entire system.
Solution Approach 2:
The patent introduces an intermediary processing stage where first SAO information is coded by context adaptive binary arithmetic coding and second SAO information is coded by bypass arithmetic coding. This intermediary approach acts as a bridge between traditional sequential processing and modern parallel processing requirements, enabling both simplicity and parallel capability.
3Reliability
If redundant bit lengths are not reduced, then coding robustness is maintained, but bit stream efficiency deteriorates
Solution Approach 1:
The patent applies different coding precision and compression strategies to different parts of the SAO information. The first SAO information uses context adaptive coding that achieves high compression efficiency for category indices and positions, while the second SAO information uses bypass coding that efficiently represents offset values. This local optimization reduces overall bit length without compromising the robustness of critical information.
Solution Approach 2:
The patent changes the coding parameters and methods applied to different SAO information types. By using context adaptive binary arithmetic coding for first SAO information and bypass arithmetic coding for second SAO information, the patent optimizes the bit representation parameters to reduce redundant bits while maintaining coding robustness through appropriate method selection.
Data Source
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AI summary
A moving picture coding method includes: performing context adaptive binary arithmetic coding in which a variable probability value is used, on first information among multiple types of sample adaptive offset (SAO) information used for SAO that is a process of assigning an offset value to a pixel value of a pixel included in an image generated by coding the input image (S11); and continuously performing bypass arithmetic coding in which a fixed probability value is used, on second information and third information among the multiple types of the SAO information (S12), wherein the coded second and third information are placed after the coded first information in the bit stream.