Multi-Residue Block Coding for Video Compression
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Solution Overview
Problem
Current video coding technologies face challenges in efficiently compressing video data while maintaining video quality, particularly due to limited bandwidth and memory resources, and existing methods do not effectively utilize multiple residual blocks to reduce coding overhead and improve reconstruction accuracy.
Innovation Solution
The proposed solution involves deriving multiple residual blocks using independent sets of parameters, combining them to form a combined residual block, and using this combined block to reconstruct the original block, which can include different transform sizes, types, and coding modes, such as lossless or lossy coding, to reduce coding overhead and improve video quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple residual blocks are coded and combined to reconstruct a current block, then video quality and compression efficiency are improved, but device complexity and processing overhead increase
Solution Approach 1:
The residual block is segmented into multiple partial residual blocks, each processed with different transform types and sizes. This segmentation allows the encoder to capture different frequency components more effectively, improving compression efficiency while distributing the processing load across multiple simpler transform operations rather than one complex transform.
Solution Approach 2:
Multiple partial residual blocks with different transform characteristics are combined through addition to form the final reconstructed block. This merging strategy allows the system to leverage the strengths of different transform types (e.g., DCT for smooth regions, DST for edge regions) simultaneously, improving overall video quality and compression efficiency.
2Measurement precision
If different transform sizes and types are applied to residual blocks, then coding precision and video quality are improved, but device complexity increases
Solution Approach 1:
Different transform types and sizes are applied to different partial residual blocks based on their local characteristics. For example, DCT transforms are applied to blocks with smooth variations while DST transforms are applied to blocks with sharp edges. This local adaptation improves coding precision by matching the transform type to the local content characteristics, while avoiding the need to manage complex global transform parameters.
Solution Approach 2:
The system dynamically changes transform parameters (type and size) for different partial residual blocks based on content analysis. This parameter adaptation allows the encoder to optimize for local characteristics without requiring a single complex transform configuration, thereby improving precision while keeping individual transform operations relatively simple and manageable.
Data Source
AI summary
The various implementations described herein include methods and systems for coding video. In one aspect, a method includes receiving a video bitstream comprising a plurality of coding blocks including a current block. The method includes deriving a first residual block for the current block using a first set of parameters. The method includes deriving a second residual block for the current block using a second set of parameters, where the second set of parameters is independent of the first set of parameters. The method includes deriving a combined residual block using the first residual block and the second residual block. The method also includes reconstructing the current block using the combined residual block.