Adaptive Loop Filter Coefficient Coding With Position-Based Short Codes
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Solution Overview
Problem
The existing video coding standards, such as HEVC, face challenges in efficiently encoding and decoding adaptive loop filter (ALF) coefficients due to filter position-dependent entropy coding and large worst-case codeword lengths, which are difficult for processors to handle, especially for 32- and 64-bit architectures.
Innovation Solution
Implementing coefficient position-independent and dependent entropy coding techniques using exp-Golomb codes, fixed length codes, and combinations thereof, to reduce codeword lengths and improve encoding and decoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If filter position-dependent entropy coding is used for ALF coefficients, then coding precision is improved, but device complexity increases and processing difficulty increases
Solution Approach 1:
The patent segments the ALF coefficient coding process by dividing coefficients into different groups based on their positions (e.g., edge coefficients vs. non-edge coefficients). Each group is assigned a different entropy coding method or parameter set, allowing precise coding for each position type while simplifying the overall processing through systematic categorization.
Solution Approach 2:
The patent applies local quality by using different entropy coding strategies for different coefficient positions. Specifically, coefficients at certain positions (e.g., edge positions) use one coding method while others use a different method, optimizing precision for each local region's characteristics rather than applying a uniform approach.
2Measurement precision
If filter position-dependent entropy coding is used for ALF coefficients, then coding precision is improved, but ease of operation deteriorates
Solution Approach 1:
By segmenting coefficients into predefined position groups, the patent automates the selection of coding methods, reducing manual configuration complexity and making the system easier to operate while maintaining high coding precision through position-specific optimization.
Solution Approach 2:
The patent enables the coding system to automatically adapt to different coefficient positions without requiring manual intervention. The encoder and decoder self-configure their coding strategies based on the position information embedded in the data structure, improving ease of operation while preserving coding precision.
3Measurement precision
If large worst-case codeword lengths are used for ALF coefficients, then measurement precision is improved, but productivity decreases and device complexity increases
Solution Approach 1:
The patent changes the parameters of the entropy coding system by introducing position-dependent coding modes that adjust codeword length based on coefficient position. This allows the system to use longer codewords only when necessary for precision while using shorter codewords for other positions, thereby improving overall processing efficiency and productivity.
Solution Approach 2:
Instead of applying maximum precision coding to all coefficients, the patent applies precise coding selectively only to coefficients where it is most beneficial (e.g., edge coefficients), while using more compact coding for others. This partial application of high-precision coding maintains necessary measurement precision while significantly improving processing efficiency.
4Measurement precision
If filter position-dependent entropy coding is used for ALF coefficients, then coding precision is improved, but difficulty of detecting and measuring increases
Solution Approach 1:
The patent segments the decoding process into distinct stages corresponding to different coefficient position groups. Each segment has its own decoding rules and parameter interpretations, making the overall complex process more manageable and easier to detect and measure by breaking it into standardized, repeatable segments.
Solution Approach 2:
The patent creates a universal decoding framework that handles different coefficient positions through a unified structure. The same basic decoding algorithm is applied universally, with position-specific parameters automatically selected based on the data structure, reducing the difficulty of detecting and measuring by eliminating the need for multiple specialized decoding paths.
Data Source
AI summary
A method for adaptive loop filtering is provided that includes determining a coefficient value for each coefficient position of an adaptive loop filter, applying the adaptive loop filter to at least a portion of a reconstructed picture using the coefficient values, and entropy encoding coefficient values into a compressed bit stream using predetermined short binary codes, wherein the short binary code used depends on the coefficient position of the coefficient value.