Adaptive Quantization Control for Video Compression Quality
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Solution Overview
Problem
Existing video compression algorithms suffer from information loss due to quantization, particularly affecting image quality, and there is a need for real-time adaptive quantization control to enhance subjective picture quality.
Innovation Solution
A video encoder with a quantization controller that dynamically adjusts the quantizer scale based on the complexity of macro blocks, using diagonal frequency detection, luma level detection, and motion level detection to apply a weighted function and generate a new quantizer scale, thereby providing real-time adaptive quantization control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If quantization is applied during video compression to reduce bit rate, then the bit rate is reduced, but information loss increases and image quality deteriorates
Solution Approach 1:
The patent applies different quantization coefficients to different macro blocks based on their characteristics. Specifically, it distinguishes between static and moving macro blocks, applying stronger quantization (larger coefficients) to static blocks and weaker quantization (smaller coefficients) to moving blocks. This local differentiation allows the system to reduce overall bit rate while preserving important motion information, thereby reducing information loss in critical areas.
Solution Approach 2:
The patent dynamically adjusts quantization coefficients based on real-time analysis of macro block characteristics. The system continuously evaluates whether each macro block is static or moving and adapts the quantization strength accordingly. This dynamic adjustment allows the compression algorithm to optimize the balance between bit rate reduction and information preservation for each specific block rather than applying a uniform quantization strategy.
2Ease of manufacture
If uniform quantization is applied to all macro blocks, then the encoding process is simple, but image quality deteriorates in both static and moving areas
Solution Approach 1:
The patent segments the video content into different macro blocks and further classifies each block as either static or moving. This segmentation allows the application of different quantization strategies to different regions of the video content. By dividing the content and applying tailored quantization to each segment, the system achieves better image quality preservation while maintaining relatively simple encoding logic through clear classification rules.
3Productivity
If strong quantization is applied to reduce bit rate, then compression efficiency improves, but subjective picture quality deteriorates
Solution Approach 1:
The patent changes the quantization parameter (quantization coefficient) based on the characteristics of each macro block. By adjusting this critical parameter dynamically - using larger coefficients for static blocks and smaller coefficients for moving blocks - the system optimizes compression efficiency for each region. This parameter adaptation allows the achievement of better compression efficiency overall while preserving subjective picture quality in motion-critical areas.
Data Source
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AI summary
A system and method for controlling video compression quantization comprising generating a quantizer scale offset based on diagonal frequencies of luminance components of a data block samples, luminance intensity of the samples and motion activity of the data block, adjusting a first quantizer scale using the quantizer scale offset to receive a second quantizer scale and quantizing the data block using the second quantizer scale.