Last-Position Image Coding With Bit-Specific Arithmetic Contexts
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Solution Overview
Problem
Conventional video coding standards face challenges in accurately switching contexts during context adaptive binary arithmetic coding and decoding, leading to decreased coding efficiency due to inappropriate context selection for binary symbols with different probability occurrences.
Innovation Solution
An image coding method that binarizes last position information and uses context adaptive binary arithmetic coding, switching contexts based on bit positions and employing a fixed probability for certain signals, with the binary symbol at the last bit position coded using a context exclusive to that position, to enhance coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single context is used for all binary symbols in context adaptive binary arithmetic coding, then the device complexity is reduced, but the coding efficiency decreases due to inaccurate probability prediction for symbols with different occurrence probabilities
Solution Approach 1:
The patent applies local quality by using different contexts for different bit positions in the binary signal. Specifically, binary symbols at different positions (e.g., first bit position vs. second bit position) are coded using different contexts that are adapted to their local probability characteristics. This allows each local region (bit position) to have its own optimized context, improving probability prediction accuracy without requiring a single complex global context model.
Solution Approach 2:
The patent segments the binary signal into multiple parts based on bit positions, where each segment is coded using a dedicated context. For example, the binary signal is divided into segments corresponding to different bit positions (first bit, second bit, etc.), and each segment is processed independently with its own context model. This segmentation allows the system to handle different probability distributions in different segments without increasing overall device complexity.
2Productivity
If context adaptive binary arithmetic coding is used for all binary symbols, then the coding efficiency is improved, but the processing speed decreases due to the complexity of context switching
Solution Approach 1:
The patent segments the binary signal into multiple parts based on bit positions, where each segment is coded using a dedicated context. For example, the binary signal is divided into segments corresponding to different bit positions (first bit, second bit, etc.), and each segment is processed independently with its own context model. This segmentation allows the system to handle different probability distributions in different segments without increasing overall device complexity.
Solution Approach 2:
The patent applies local quality by using different contexts for different bit positions in the binary signal. Specifically, binary symbols at different positions (e.g., first bit position vs. second bit position) are coded using different contexts that are adapted to their local probability characteristics. This allows each local region (bit position) to have its own optimized context, improving probability prediction accuracy without requiring a single complex global context model.
Data Source
AI summary
An image coding method including: binarizing last position information to generate (i) a binary signal which includes a first signal having a length smaller than or equal to a predetermined maximum length and does not include a second signal or (ii) a binary signal which includes the first signal having the predetermined maximum length and the second signal; first coding for arithmetically coding each of binary symbols included in the first signal using a context switched among a plurality of contexts according to a bit position of the binary symbol; and second coding for arithmetically coding the second signal using a fixed probability when the binary signal includes the second signal, wherein in the first coding, a binary symbol at a last bit position of the first signal is arithmetically coded using a context exclusive to the last bit position, when the first signal has the predetermined maximum length.