Luma QP Derivation for Block-Based Image Compression
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Solution Overview
Problem
The increasing demand for high-resolution, high-quality images results in higher transmission and storage costs due to increased data volume, necessitating a more efficient image compression technique.
Innovation Solution
A method for deriving a quantization parameter (QP) using an expected average luma value and a quantization parameter offset, applied in image coding systems to enhance compression efficiency through inverse quantization and prediction processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high-resolution, high-quality images are transmitted or stored, then image quality and resolution are improved, but transmission cost and storage cost increase
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the quantization parameter (QP) based on the luma value characteristics of image blocks. By deriving QP offsets from expected average luma values and neighboring sample statistics, the system adapts the quantization strength to local image characteristics, achieving better compression efficiency while maintaining perceived image quality.
2Device complexity
If a fixed quantization parameter is used for all blocks, then encoding complexity is reduced, but quantization efficiency deteriorates
Solution Approach 1:
The patent implements local quality by deriving different quantization parameters for different blocks based on their local luma characteristics. The QP offset is calculated using the expected average luma value of neighboring samples, allowing each block to have a customized QP that matches its local brightness characteristics, thereby improving quantization efficiency without significantly increasing complexity.
Solution Approach 2:
The patent applies preliminary action by pre-calculating the expected average luma value from neighboring available samples before performing the actual quantization. This preliminary derivation of luma statistics enables the system to determine appropriate QP offsets in advance, optimizing the quantization process for each block while maintaining encoding efficiency.
Data Source
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AI summary
According to an embodiment of the present invention, a picture decoding method performed by a decoding apparatus is provided. The method comprises: decoding image information comprising information on a quantization parameter (QP), deriving an expected average luma value of a current block from neighboring available samples, deriving a quantization parameter offset (QP offset) for deriving a luma quantization parameter (luma QP) based on the expected average luma value and the information on the QP, deriving the luma QP based on the QP offset, performing an inverse quantization for a quantization group comprising the current block based on the derived luma QP, generating residual samples for the current block based on the inverse quantization, generating prediction samples for the current block based on the image information and generating reconstructed samples for the current block based on the residual samples for the current block and the prediction samples for the current block.