Cross-Component Sample Offset for Lower-Bitrate Video Coding
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Solution Overview
Problem
Existing video coding standards face challenges in efficiently encoding and decoding high-definition and ultra-high-definition video data while maintaining image quality, particularly in optimizing the coding efficiency of luma and chroma components.
Innovation Solution
The method involves transforming samples of one color component into another color space, determining a sample offset using a classifier, and modifying the sample values based on this offset to enhance coding efficiency by leveraging cross-component relationships between luma and chroma components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional video coding standards are used for encoding high-definition and ultra-high-definition video data, then the encoding process is relatively simple, but the coding efficiency is insufficient and image quality deteriorates
Solution Approach 1:
The patent transforms video samples from one color space to another color space to change the representation parameters of the video data. This parameter transformation enables more efficient coding by exploiting the statistical properties and correlations in the transformed domain, thereby improving coding efficiency while maintaining or enhancing image quality for high-definition and ultra-high-definition video data.
2Loss of energy
If cross-component sample adaptive offset is applied to improve coding efficiency, then bit-rate requirements are reduced, but the complexity of the encoding and decoding process increases
Solution Approach 1:
The patent applies cross-component sample adaptive offset by transforming samples of one color component into another color space and determining sample offsets based on classifier information. This approach reduces bit-rate requirements by efficiently exploiting cross-component correlations, while the use of standardized transformation and classification procedures keeps the increased complexity manageable.
Data Source
AI summary
An electronic apparatus performs a method of decoding video data, comprising: receiving, from the video signal, a picture frame that includes a first component and a second component in a first color space; determining a classifier for the second component in the first color space from a set of one or more samples of the first component associated with a respective sample of the second component in the first color space, wherein the set of one or more samples are in a second color space; determining a sample offset for the respective sample of the second component in the first color space according to the classifier; and modifying the value of the respective sample of the second component in the first color space based on the determined sample offset.