Luma QP Derivation Using Average Brightness for Image Coding
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images leads to increased transmission and storage costs due to the higher amount of information required, necessitating a more efficient image compression technique.
Innovation Solution
A method and apparatus for enhancing video coding efficiency by deriving a quantization parameter (QP) using an expected average luma value and a quantization parameter offset, and applying inverse quantization to generate residual and prediction samples for improved image reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high-resolution, high-quality image data is transmitted or stored, then image quality and resolution are improved, but transmission cost and storage cost increase
Solution Approach 1:
The patent changes the quantization parameter (QP) dynamically based on the average luma value of the current block. By adjusting QP according to luminance characteristics, the system achieves better compression efficiency while maintaining image quality, thus reducing the amount of data needed to represent high-quality images.
Solution Approach 2:
The patent applies different quantization parameters to different blocks based on their local luminance characteristics. Blocks with different average luma values receive different QP adjustments, allowing for optimized compression at each local region while preserving overall image quality.
2Manufacturing precision
If high-resolution, high-quality image data is transmitted or stored, then image quality and resolution are improved, but transmission cost and storage cost increase
Solution Approach 1:
By dynamically adjusting the quantization parameter based on average luma value, the system optimizes the balance between compression ratio and image quality. This reduces the total bit rate required for transmission, thereby lowering transmission costs while maintaining high image quality.
3Productivity
If conventional quantization parameter derivation is used, then coding simplicity is maintained, but quantization efficiency is insufficient
Solution Approach 1:
The patent modifies the quantization parameter derivation process by incorporating average luma value calculations and offset adjustments. This enhances quantization efficiency by adapting QP to local image characteristics, while the additional complexity remains computationally manageable through efficient algorithms.
Solution Approach 2:
The patent performs preliminary calculation of average luma value for each block before the actual quantization process. This pre-computation allows for optimized quantization parameter selection, improving overall quantization efficiency without significantly increasing total processing complexity.
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.