Secondary Video Transform Selection for Lower Coding Complexity
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Solution Overview
Problem
Next-generation video contents with high spatial resolution, high frame rate, and high dimensionality require more efficient memory storage, memory access rate, and processing power, necessitating improved coding tools, particularly in transform efficiency and complexity.
Innovation Solution
A method for configuring a secondary transform set considering various conditions, including intra prediction mode and coding block size, with mixed secondary transform sets comprising 8×8 and 4×4 transform kernels, and a binarized secondary transform index using a truncated unary scheme.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional transform methods are used for next-generation video contents, then processing can be performed with existing tools, but memory storage, memory access rate, and processing power requirements increase tremendously
Solution Approach 1:
The patent applies parameter changes by modifying the transform block size parameter (using 4×4 sub-blocks instead of traditional larger blocks) and adapting the transform type based on prediction mode parameters. This allows the system to process high-resolution video content while reducing memory storage requirements and processing complexity through optimized transform parameters.
2Productivity
If more efficient coding tools are designed for next-generation video contents, then processing efficiency improves, but the complexity of the coding system increases
Solution Approach 1:
The patent implements dynamics by adaptively selecting transform types and block sizes based on the intra prediction mode of the current block. The system dynamically adjusts the transform parameters: using 4×4 NSST for certain prediction modes and 4×4 DST otherwise, and selecting between different secondary transform types based on block size. This adaptive approach improves coding efficiency while managing system complexity through conditional logic rather than fixed complex structures.
3Productivity
If transform is applied with higher efficiency, then coding efficiency improves, but computational complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the transform block into 4×4 sub-blocks and applying secondary transform only to specific sub-blocks based on the intra prediction mode. This segmentation allows the system to process only necessary portions of the block with enhanced transforms, improving coding efficiency while reducing overall computational complexity by avoiding unnecessary transformations on entire blocks.
Solution Approach 2:
The patent implements local quality by applying different transform types to different regions of the video block based on local characteristics (intra prediction mode). Specifically, 4×4 NSST is applied to 4×4 luma blocks when the intra prediction mode is in certain ranges, while 4×4 DST is applied otherwise. This localized adaptive transformation optimizes coding efficiency for specific regions without unnecessarily increasing complexity across the entire block.
Data Source
AI summary
Disclosed is a method for decoding a video signal, including: generating a dequantized transform block by performing dequantization for a current block; acquiring an intra prediction mode of the current block; determining a secondary transform set applied to the current block among a plurality of secondary transform sets based on the intra prediction mode; deriving a transform kernel applied to the current block in the determined secondary transform set; and performing secondary transform for a top left specific area of the dequantized transform block by using the derived transform kernel, in which the plurality of secondary transform sets may include at least one mixed secondary transform set.