Image Encoding With Adaptive Quantization Matrices for Rectangular Blocks
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Solution Overview
Problem
The increasing complexity of quantization matrices for rectangular orthogonal transformations in VVC encoding methods leads to an unnecessary increase in code amount, which affects encoding efficiency.
Innovation Solution
Generating a second quantization matrix from a first quantization matrix of size N×N to accommodate rectangular sub-blocks of sizes P×Q, where P and Q are positive integers, allowing for efficient quantization and inverse quantization of transformation coefficients in sub-blocks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If quantization matrices are individually defined for all orthogonal transformation shapes, then the encoding precision for different transformation shapes is improved, but the code amount of quantization matrices unnecessarily increases
Solution Approach 1:
The patent applies universality by defining a single quantization matrix that can be used across multiple orthogonal transformation shapes (square and rectangular). Instead of creating separate quantization matrices for each transformation type, the invention uses one universal quantization matrix that adapts to different shapes, thereby reducing the total code amount while maintaining encoding precision for various transformation shapes.
2Productivity
If the basic block size is increased to improve encoding efficiency, then the processing speed is improved, but the complexity of handling different sub-block shapes increases
Solution Approach 1:
The patent applies segmentation by dividing the basic block into multiple sub-blocks of different shapes (square and rectangular) and applying appropriate orthogonal transformations to each. This allows the system to handle larger basic blocks for improved encoding efficiency while managing the complexity through systematic segmentation and shape-specific processing of sub-blocks.
Data Source
AI summary
An image encoding apparatus for encoding an image comprises a generation unit configured to generate, from a first quantization matrix having a size of N×N (N is a positive integer), a second quantization matrix having a size of P×Q (P and Q are positive integers which satisfy P<N<Q, and the size of P×Q indicates a size of P in a horizontal direction and a size of Q in a vertical direction), and a quantization unit configured to quantize transformation coefficients in a sub-block having a size corresponding to the size of P×Q using the second quantization matrix.