Image Coding Context Switching for Last Position Binarization
Find Innovative SolutionsGenerate Solutions
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 the use of common contexts for bit positions with significantly different symbol occurrence probabilities.
Innovation Solution
An image coding method that binarizes last position information to generate a binary signal with a context-switched coding approach, where binary symbols at specific bit positions are coded using contexts exclusive to those positions, and uses a fixed probability for certain signal components, optimizing coding efficiency by varying the signal length based on block size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a common context is used for binary symbols at different bit positions, then the device complexity is reduced, but the coding efficiency decreases due to inaccurate probability prediction
Solution Approach 1:
The patent applies local quality by assigning different contexts to different bit positions within the binary signal. Specifically, binary symbols at the first bit position use one context, while binary symbols at the second and subsequent bit positions use another context. This allows each bit position to be coded with a context appropriate to its local characteristics, improving probability prediction accuracy and coding efficiency without requiring excessive complexity.
2Productivity
If context adaptive binary arithmetic coding is used for all binary symbols, then the coding efficiency is improved, but the memory requirements increase
Solution Approach 1:
The patent segments the binary signal into different parts based on bit position, applying context adaptive binary arithmetic coding only to specific segments (first bit position and second bit position with different contexts). This segmentation allows the system to achieve coding efficiency improvements where they are most needed while limiting the application of complex context adaptive methods to specific portions of the data, thereby controlling memory requirements.
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.