Directional Transform-Skip Quantization for Video Compression
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Solution Overview
Problem
Existing video coding technologies face inefficiencies in intra prediction and motion vector prediction, leading to suboptimal compression ratios and increased data requirements, particularly in high-definition video applications.
Innovation Solution
Implementing a transform skip mechanism for video encoding and decoding, where transform coefficients are de-quantized using varying quantization steps based on direction, allowing for efficient processing of transform blocks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If transform coefficients are de-quantized using a single quantization step, then the processing is simple, but the compression efficiency is suboptimal
Solution Approach 1:
The patent segments the transform coefficients into different groups based on their spatial frequency characteristics (DC coefficients, low-frequency coefficients, high-frequency coefficients). Each group is then de-quantized using a different quantization step, allowing optimized compression for each frequency band while maintaining manageable processing complexity through systematic categorization.
Solution Approach 2:
The patent applies different quantization steps to different spatial frequency components of the transform coefficients. Specifically, DC coefficients use one quantization step, low-frequency coefficients use another, and high-frequency coefficients use a third. This local differentiation optimizes compression efficiency by preserving important low-frequency information while aggressively compressing less important high-frequency information.
2Measurement precision
If more bits are used to represent intra prediction directions and motion vectors, then the prediction accuracy is improved, but the data volume increases
Solution Approach 1:
The patent applies partial action by using different quantization precision for different coefficient groups. Instead of uniformly applying high precision to all coefficients, it applies higher precision (smaller quantization steps) only to DC and low-frequency coefficients which contribute most to prediction accuracy, while using coarser quantization for high-frequency coefficients. This achieves good prediction accuracy with reduced data volume.
Solution Approach 2:
The patent changes the quantization parameter (quantization step size) based on the spatial frequency of the coefficients. By dynamically adjusting the quantization parameter according to the coefficient group, the system optimizes the balance between prediction accuracy and data volume, using finer quantization where needed and coarser quantization where acceptable.
Data Source
AI summary
Aspects of the disclosure provide a method and an apparatus including processing circuitry for video decoding. The processing circuitry can be configured to determine a transform skip for a transform block (TB) is in one direction. The processing circuitry can be configured to quantize transform coefficients in the TB based on a plurality of quantization steps. First transform coefficients in the TB can be quantized based on a smallest of the plurality of quantization steps. The first transform coefficients in the TB include one of a first row and a first column of the transform coefficients in the TB that has a DC spatial frequency, the one of the first row and the first column being along the one direction of the transform skip. Further, the processing circuitry can be configured to perform a transform on the quantized transform coefficients in the TB.