Multidimensional Quantization for Video Coding Efficiency
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Solution Overview
Problem
Existing video compression systems lack flexibility in controlling in-loop quantization, allowing only single-dimensional quantization of transform coefficients at a block or macroblock level, which limits coding efficiency and quality.
Innovation Solution
The proposed solution involves quantizing input video data along multiple dimensions, including pixel residuals, transform coefficients, and entropy coding, using multiple quantizers in parallel or cascade configurations, allowing for sub-frame level selection of quantization parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If single-dimensional quantization of transform coefficients is used, then device complexity is reduced, but coding efficiency and quality are limited
Solution Approach 1:
The quantization process is segmented into multiple independent dimensions: residual quantization operates on pixel residuals before transform, while coefficient quantization operates on transform coefficients after transform. This segmentation allows each quantizer to be optimized independently, improving overall coding efficiency without proportionally increasing complexity.
Solution Approach 2:
The invention transitions from single-dimensional quantization (only transform coefficients) to multi-dimensional quantization by adding a second dimension (pixel residuals). This dimensional expansion enables more flexible rate-distortion optimization and improves coding efficiency.
2Productivity
If multiple quantizers are used in parallel or cascade configurations, then coding efficiency is improved, but device complexity increases
Solution Approach 1:
The system dynamically selects between different quantization configurations (parallel or cascade) and adjusts quantization parameters at sub-frame levels based on content characteristics and bitrate requirements. This dynamic adaptability optimizes coding efficiency while managing complexity through selective activation.
Solution Approach 2:
Multiple quantization parameters (QRes for residual quantization, QCoef for coefficient quantization) can be independently adjusted at sub-frame levels. This parameter flexibility allows fine-tuning of the trade-off between compression efficiency and quality without requiring structural changes to the quantization framework.
3Adaptability or versatility
If quantization parameters are selected at sub-frame levels, then adaptability is improved, but device complexity increases
Solution Approach 1:
The video frame is segmented into sub-frames, allowing independent quantization parameter selection for each sub-frame. This segmentation enables localized optimization based on content characteristics while keeping the control granularity manageable.
Solution Approach 2:
Instead of applying uniform quantization parameters across entire frames, the system applies partial optimization at sub-frame levels where it provides the most benefit. This selective approach improves adaptability while avoiding the excessive complexity of full-frame independent control.
Data Source
AI summary
Video compression and decompression techniques are disclosed that provide improved bandwidth control for video compression and decompression systems. In particular, video coding and decoding techniques quantize input video in multiple dimensions. According to these techniques, pixel residuals may be generated from a comparison of an array of input data to an array of prediction data. The pixel residuals may be quantized in a first dimension. After the quantization, the quantized pixel residuals may be transformed to an array of transform coefficients. The transform coefficients may be quantized in a second dimension and entropy coded. Decoding techniques invert these processes. In still other embodiments, multiple quantizers may be provided upstream of the transform stage, either in parallel or in cascade, which provide greater flexibility to video coders to quantize data in different dimensions in an effort to balance the competing interest in compression efficiency and quality of reconstructed video.