Transform Kernel Sharing for Video Coding
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently reducing redundancy in video signals while maintaining acceptable distortion levels, particularly in high-resolution and high-frame-rate video streams.
Innovation Solution
The proposed solution involves a method for transform kernel sharing in video encoding and decoding, where a set of transform kernels with shared high-frequency basis vectors and individualized low-frequency basis vectors are used to process video data blocks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If traditional video coding techniques are used to compress high-resolution high-frame-rate video, then bandwidth and storage requirements are reduced, but distortion between original and reconstructed signals increases
Solution Approach 1:
The video signal is segmented into multiple blocks that are processed independently through transform coding. Each block is transformed into frequency domain coefficients, allowing selective compression of different frequency components while maintaining overall signal fidelity within acceptable distortion limits
Solution Approach 2:
The transform kernel parameters are optimized to achieve better energy compaction in the frequency domain. By adjusting transform parameters and using adaptive quantization, the coding system achieves higher compression ratios while controlling the distortion between original and reconstructed signals
2Productivity
If multiple transform kernels are used to improve compression performance, then coding efficiency increases, but memory requirements for storing transform kernels increase
Solution Approach 1:
Multiple transform kernels are merged into a single unified transform kernel through adaptive weighting and combination techniques. The system dynamically selects and combines basis functions from multiple kernels to achieve compression performance comparable to using multiple separate kernels, while storing only one combined kernel in memory
Solution Approach 2:
A single transform kernel is designed to serve multiple functions by incorporating adaptive parameters that allow it to behave like different specialized kernels depending on the input block characteristics. This universal kernel can adapt to various video content types (intra-picture, inter-picture, different frequencies) without requiring separate dedicated kernels for each case
Data Source
AI summary
This disclosure relates to a transform kernel sharing in video encoding and decoding. For example, a method is disclosed for such transform kernel sharing. The method may include identifying a plurality of transform kernels, wherein each of the plurality of transform kernels comprises a set of basis vectors from low to high frequencies; N high-frequency basis vectors of two or more of the plurality of transform kernels are shared, N being a positive integer; and low-frequency basis vectors of the two or more of the plurality of the transform kernels other than the N high-frequency basis vectors are individualized. The method may further include extracting a data block from a video bitstream; selecting a transform kernel from the plurality of transform kernels based on information associated with the data block; and applying the transform kernel to at least a portion of the data block to generate a transformed block.