Image Decoding Context Switching for Last Position Coding

Solution Overview

Problem

Conventional video coding standards face challenges in accurately switching contexts during context adaptive binary arithmetic coding and decoding of last position information, leading to decreased coding efficiency due to inappropriate context selection for bit positions with different symbol occurrence probabilities.

Innovation Solution

The method involves binarizing last position information into binary signals with a prefix part and an optional suffix part, where each binary symbol in the prefix part is coded using a context switched among multiple contexts based on its bit position, and the suffix part is coded using a fixed probability, with the binary symbol at the last bit position of the prefix part being coded using a context exclusive to that position.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If a single context is used for all binary symbols in the prefix part, then device complexity is reduced, but coding efficiency deteriorates due to inaccurate probability prediction for bits with different symbol occurrence probabilities

Engineering Contradiction:

Improvecontext management complexityVSAvoidcoding efficiency

Core Design Contradiction:

Device complexityVSProductivity

Solution Approach 1:

The patent segments the prefix part into multiple groups based on bit position, with each group assigned a dedicated context. This segmentation allows different contexts to capture the distinct symbol occurrence probability characteristics of different bit positions, thereby improving coding efficiency while maintaining manageable device complexity through systematic organization.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies local quality by assigning different contexts to different bit positions within the prefix part. Each context is optimized for the specific statistical characteristics of its associated bit positions, enabling more accurate probability predictions locally rather than using a uniform approach across all bits.

Inventive Principle:

Principle #3Local quality

2Productivity

If multiple contexts are used for binary symbols in the prefix part, then coding efficiency is improved through accurate probability prediction, but device complexity increases due to additional context management

Engineering Contradiction:

Improvecoding efficiencyVSAvoidcontext management complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent segments the prefix part into multiple groups based on bit position, with each group assigned a dedicated context. This segmentation allows different contexts to capture the distinct symbol occurrence probability characteristics of different bit positions, thereby improving coding efficiency while maintaining manageable device complexity through systematic organization.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies local quality by assigning different contexts to different bit positions within the prefix part. Each context is optimized for the specific statistical characteristics of its associated bit positions, enabling more accurate probability predictions locally rather than using a uniform approach across all bits.

Inventive Principle:

Principle #3Local quality

3Productivity

If context adaptive binary arithmetic coding is used for all binary symbols, then coding efficiency is improved, but memory requirements increase due to storing multiple context probability tables

Engineering Contradiction:

Improvecoding efficiencyVSAvoidmemory requirements

Core Design Contradiction:

ProductivityVSQuantity of substance

Solution Approach 1:

The patent segments the prefix part into multiple groups based on bit position, with each group assigned a dedicated context. This segmentation allows different contexts to capture the distinct symbol occurrence probability characteristics of different bit positions, thereby improving coding efficiency while maintaining manageable device complexity through systematic organization.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies local quality by assigning different contexts to different bit positions within the prefix part. Each context is optimized for the specific statistical characteristics of its associated bit positions, enabling more accurate probability predictions locally rather than using a uniform approach across all bits.

Inventive Principle:

Principle #3Local quality

Data Source

PatentEP3849198B1Image decoding method and image decoding device

Publication Date: 2022.12.28 TAGIVAN II

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AI summary

An image coding method including: binarizing (S401) 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 (S402) 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 (S404) 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.