Transform Coefficient Level Coding for Pipelined Video Decoding
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Solution Overview
Problem
Current video coding standards, such as H.264/AVC and the developing HEVC, face inefficiencies in encoding and decoding transform coefficients due to throughput issues at the upper-left and bottom-right corners of coefficient groups, particularly with diagonal scan orders, leading to pipelining problems and suboptimal compression efficiency.
Innovation Solution
The use of distinct context templates specific to horizontal and vertical scan orders ensures that neighboring positions are at least three scan order positions previous to the current position, allowing for pipelining by fully processing required data in the context template, and adaptive threshold-based level decoding is employed to optimize coefficient level encoding and decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If diagonal scan order is used for encoding transform coefficients, then compression efficiency is improved, but throughput and pipelining performance deteriorate due to bottlenecks at upper-left and bottom-right corners
Solution Approach 1:
The transform coefficient block is divided into multiple sub-blocks, and different scan orders are applied to different sub-blocks. Specifically, diagonal scan order is used for some sub-blocks to maintain compression efficiency, while horizontal or vertical scan orders are used for other sub-blocks to improve throughput and eliminate pipelining bottlenecks at corner positions.
Solution Approach 2:
Different scan orders are applied locally to different regions of the transform coefficient block based on their specific characteristics. The upper-left and bottom-right corner sub-blocks use horizontal or vertical scan orders to avoid pipelining issues, while other regions may benefit from diagonal scan order for better compression.
2Loss of information
If diagonal scan order is used for encoding transform coefficients, then compression efficiency is improved, but encoding and decoding time increases due to pipelining problems
Solution Approach 1:
The transform coefficient block is divided into multiple sub-blocks, and different scan orders are applied to different sub-blocks. Specifically, diagonal scan order is used for some sub-blocks to maintain compression efficiency, while horizontal or vertical scan orders are used for other sub-blocks to improve throughput and eliminate pipelining bottlenecks at corner positions.
3Measurement precision
If context templates are designed to include neighboring positions for adaptive coding, then coding accuracy is improved, but pipelining capability deteriorates due to data dependency
Solution Approach 1:
The context modeling is segmented by applying different context templates to different sub-blocks. For sub-blocks where pipelining is critical (such as those at corner positions), simplified context templates are used that do not require future neighboring data. For other sub-blocks, full adaptive context templates are used to maximize coding accuracy.
Solution Approach 2:
Context templates are designed to use only previously decoded neighboring positions rather than future positions. This preliminary action approach ensures that all context data is available before encoding the current coefficient, enabling pipelining without data dependency bottlenecks.
Data Source
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AI summary
Methods and devices for reconstructing coefficient levels from a bitstream of encoded video data for a coefficient group in a transform unit, using adaptive-threshold-based level coding. Threshold is set based upon level information from one or more previously-reconstructed coefficient groups in the transform unit. Threshold may be maximum number of level flags to decode for the coefficient group. Level information may include number of level flags decoded in previous coefficient groups. Previously-reconstructed coefficient groups may include coefficient group to the right and below the current coefficient group.