Selective Color Space Conversion for Efficient Image Block Encoding
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images leads to a significant increase in transmission and storage costs due to the rise in the amount of transmitted information, necessitating a high-efficient image compression technology.
Innovation Solution
An image encoding/decoding method that performs selective color space conversion using a clipping operation to derive quantization parameters, adjusting the value of the quantization parameter within a specific range, and encoding transformation coefficients to improve encoding/decoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If color space conversion is applied to all blocks, then encoding efficiency is improved, but processing complexity and time increase
Solution Approach 1:
The patent applies color space conversion selectively only to blocks where it is beneficial (e.g., blocks with certain characteristics or in specific regions), rather than uniformly to all blocks. This partial application maintains encoding efficiency improvements while reducing overall processing time and computational complexity.
Solution Approach 2:
Different blocks are treated differently based on their local characteristics. The patent determines whether color space conversion should be applied to each block individually based on local properties such as texture complexity, edge density, or other block-specific features, optimizing the balance between compression efficiency and processing cost for each region.
2Productivity
If quantization parameter range is expanded, then compression capability is improved, but precision and quality deteriorate
Solution Approach 1:
The patent dynamically adjusts the quantization parameter range based on block characteristics, image content, and encoding conditions. Instead of using a fixed wide range, the system adapts the quantization parameters locally and adaptively to achieve optimal compression while maintaining acceptable precision and quality for each specific block.
Solution Approach 2:
The patent employs multiple quantization parameters with different ranges and characteristics for different blocks or regions. By changing the quantization parameters based on local block properties, the system can expand the range where needed for compression while maintaining precision where required for quality preservation.
3Speed
If transformation skip mode is used, then processing speed is improved, but encoding accuracy decreases
Solution Approach 1:
The patent applies transformation skip mode selectively only to blocks where the residual signal is negligible or where skipping the transformation provides sufficient accuracy, rather than universally. This maintains processing speed benefits for simple blocks while ensuring encoding accuracy is maintained for complex blocks that require full transformation processing.
Data Source
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AI summary
Provided are an image encoding/decoding method and device. An image decoding method performed by an image decoding device according to the present disclosure includes the steps of: determining a quantization parameter of the current block on the basis of whether color space conversion is applied to a residual sample of the current block; determining a transform coefficient of the current block on the basis of the quantization parameter; determining the residual sample of the current block by using the transform coefficient; and resetting the value of the residual sample on the basis of whether the color space conversion is applied.