Luma-Based Chroma Intra-Prediction Normalization
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Solution Overview
Problem
Current video coding standards, such as H.264/AVC, face inefficiencies in chroma intra-prediction, particularly in handling larger block sizes and higher frame rates, which are addressed by the development of High Efficiency Video Coding (HEVC) with luma-based chroma intra-prediction tools, but these tools require complex computations and may not optimize for parallel processing.
Innovation Solution
The method involves using a linear model to predict chroma samples based on filtered and down-sampled luma samples, with parameters α and β computed using ordinary least squares, and normalizing α to reduce computational complexity and facilitate parallel processing, allowing for efficient chroma intra-prediction in video encoders and decoders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If luma-based chroma intra-prediction is used in HEVC, then coding efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent changes the parameters of the linear model by introducing normalization of the coefficient α and modifying the prediction formula to include an offset term. This transforms the computation into a normalized form that reduces complexity while maintaining coding efficiency, directly addressing the contradiction between improved compression performance and increased computational burden
Solution Approach 2:
The patent segments the chroma prediction process into distinct steps: computing the normalized coefficient α, computing the offset term, and then applying the simplified prediction formula. This segmentation allows for more efficient computation and easier implementation in video coding systems
2Measurement precision
If complex computations are used for chroma intra-prediction, then prediction accuracy is improved, but processing time increases
Solution Approach 1:
The patent applies parameter changes by normalizing the coefficient α and reformulating the prediction equation to include an offset. This transformation reduces the number of computational operations required while maintaining prediction accuracy, thereby reducing processing time without sacrificing quality
Solution Approach 2:
The patent uses partial action by computing only the necessary components (normalized α and offset) rather than performing full complex computations. This partial approach achieves sufficient prediction accuracy with significantly reduced computational effort and processing time
3Productivity
If luma-based chroma intra-prediction is implemented, then compression efficiency is improved, but ease of implementation decreases
Solution Approach 1:
The patent simplifies implementation by changing the parameters of the linear model to include normalization and offset terms. This reformulation makes the algorithm easier to implement in practice while maintaining compression efficiency, as the normalized form reduces computational complexity and ease of integration into video coding systems
Data Source
AI summary
A method for luma-based chroma intra-prediction in a video encoder or a video decoder is provided that includes filtering reconstructed neighboring samples of a reconstructed down sampled luma block, computing parameters α and β of a linear model using the filtered, reconstructed neighboring samples of the reconstructed down sampled luma block and reconstructed neighboring samples of a corresponding chroma block, wherein the linear model is PredC[x,y]=α·RecL′[x,y]+β, wherein x and y are sample coordinates, PredC is predicted chroma samples, and RecL′ is samples of the reconstructed down sampled luma block, and computing samples of a predicted chroma block from corresponding samples of the reconstructed down sampled luma block using the linear model and the parameters.