Video Signal Processing With Adaptive Block Quantization
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Solution Overview
Problem
Existing video compression techniques often result in poor bit-rate performance due to the use of large, fixed block structures that do not efficiently partition pictures based on underlying video information.
Innovation Solution
The implementation of block-based picture fusion for contextual segmentation and processing, which segments video frames into smaller, 4×4 blocks and uses area-based block fusion to analyze and process the video content more efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If large fixed block structures (e.g., 128×128) are used for segmentation, then device complexity is reduced and ease of manufacture is improved, but encoding efficiency deteriorates and bit-rate performance worsens
Solution Approach 1:
The patent divides the picture into multiple coding tree units (CTUs) of varying sizes (e.g., 64×64, 128×128, 256×256) rather than using a single large fixed block size. This segmentation allows the encoder to adaptively select appropriate block sizes for different regions, improving encoding efficiency while maintaining implementation feasibility through a structured hierarchical approach.
Solution Approach 2:
The patent introduces dynamic block size selection where the encoder can choose different CTU sizes based on picture characteristics, region importance, and rate-distortion optimization. This dynamic adaptation allows the system to balance between computational complexity and encoding performance by adjusting block granularity according to local content requirements.
2Device complexity
If large fixed block structures are used for segmentation, then device complexity is reduced, but video quality deteriorates due to insufficient representation of video content
Solution Approach 1:
The patent applies different block sizes to different regions of the picture based on their characteristics. Important regions (e.g., faces, text) use smaller CTU sizes for higher precision representation, while less important regions use larger blocks. This local adaptation maintains video quality in critical areas while managing overall complexity.
Solution Approach 2:
The patent changes the block size parameter dynamically based on rate-distortion optimization results, picture content analysis, and region importance metrics. By adjusting this key parameter adaptively, the system achieves better video quality without requiring a uniformly complex structure throughout the entire picture.
3Speed
If uniform large block quantization is used, then processing speed is improved, but bit-rate performance deteriorates
Solution Approach 1:
The patent segments the picture into multiple CTUs with different sizes, allowing finer-grained quantization in important regions and coarser quantization in less important regions. This segmentation enables better bit-rate efficiency by preserving critical information while maintaining acceptable processing speeds through hierarchical processing of the segmented structure.
Solution Approach 2:
The patent applies different quantization parameters and block sizes to different regions based on their importance and content characteristics. This local differentiation optimizes the balance between information preservation and processing efficiency, maintaining bit-rate performance in critical areas while allowing faster processing in less critical regions.
Data Source
AI summary
A video signal processor is provided, having an inverse quantizer, an inverse transform processor, an in-loop filter; and a decoded picture buffer. The video signal processor is configured to receive a video signal including a picture comprising quantized pixels, wherein the picture includes a first region and a second region. The first region comprising a first plurality of blocks and having a first quantization parameter based on a first average measure of spatial activity information of the first plurality of blocks; and a second region comprising a second plurality of blocks and having a second quantization parameter based on a second average measure of information of the second plurality of blocks. The inverse quantizer being configured to inverse quantize the pixels of the blocks comprising the first region using the first quantization parameter and inverse quantize the pixels of the blocks comprising the second region using the second quantization parameter.