Quantization Unit for Orthogonal Transform Skip Blocks
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Solution Overview
Problem
The encoding efficiency is deteriorated when performing encoding processes on blocks with and without orthogonal transform skipping, as the characteristics between these blocks differ, leading to potential image quality reduction.
Innovation Solution
An image processing device that uses a weighting coefficient for quantizing orthogonal transform skip blocks and encodes the coefficients, with the option to transmit skip enable information and weighting coefficients, allowing for different quantization matrices for blocks with and without orthogonal transform processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If orthogonal transform skip is applied to certain blocks to improve encoding efficiency, then compression rate increases, but image quality deteriorates due to different characteristics between skipped and non-skipped blocks
Solution Approach 1:
The patent applies different quantization matrices to different block types: non-skipped blocks use a standard quantization matrix while skipped blocks use a separately optimized quantization matrix. This local differentiation allows each block type to be processed with the most appropriate parameters, maintaining image quality in skipped blocks while preserving encoding efficiency benefits.
Solution Approach 2:
The patent changes the quantization parameters specifically for orthogonal transform skip blocks by applying a dedicated quantization matrix that is optimized for the characteristics of skipped blocks. This parameter change ensures that skipped blocks, which have different statistical properties, are quantized appropriately to prevent image quality degradation.
2Device complexity
If a single quantization matrix is used for all blocks, then device complexity is reduced, but encoding efficiency deteriorates due to inability to optimize for different block characteristics
Solution Approach 1:
The patent segments the quantization process into two distinct paths: one for non-skipped blocks using a standard quantization matrix, and another for skipped blocks using a separately optimized quantization matrix. This segmentation allows the system to handle different block types with appropriate parameters without requiring a single overly complex unified matrix, thus improving encoding efficiency while keeping individual processing paths relatively simple.
Data Source
AI summary
The present disclosure relates to an image processing device and a method capable of suppressing the reduction of an image quality due to encoding/decoding. The image processing device includes: a quantization unit that when orthogonal transform processing is skipped with respect to a current block, quantizes all components of the current block using one weighting coefficient and when the orthogonal transform processing is performed on the current block, quantizes each component of the current block using a quantization matrix; an encoding unit that encodes the coefficient of the current block which is quantized by the quantization unit; and a transmission unit that transmits the coded data of the current block which is obtained by being encoded by the encoding unit. The present disclosure can be applied to, for example, an image processing device.