Image Re-encoding Using Adaptive Quantization Tables
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Solution Overview
Problem
Current video compression techniques, such as the JPEG format, have limitations in achieving high compression efficiency for high-resolution or high-quality video content, necessitating the development of methods to enhance compression performance while maintaining image quality.
Innovation Solution
A method and apparatus for re-encoding an image by obtaining a second quantization table based on the size distribution of values from a first quantization table, and using this new table to re-encode a reconstructed image, along with entropy encoding based on symbol frequency, to increase compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If JPEG format is used for image compression, then compatibility is maintained, but compression efficiency is limited
Solution Approach 1:
The patent changes the quantization parameters by creating a second quantization table with modified values based on the size distribution pattern of the first quantization table. This parameter change enables better compression efficiency while maintaining compatibility with JPEG decoding standards, as the re-encoding process still produces valid JPEG bitstreams that can be decoded by standard JPEG decoders.
2Productivity
If compression rate is increased, then storage and transmission costs are reduced, but image quality degrades
Solution Approach 1:
The patent applies local quality by creating a second quantization table where different elements are adjusted based on their position and importance in the frequency domain. The size distribution pattern analysis allows selective modification of quantization values - more aggressive quantization for less important coefficients and conservative quantization for important coefficients - thereby achieving better compression while preserving perceived image quality.
3Productivity
If quantization table values are increased to improve compression, then compression efficiency improves, but image quality deteriorates
Solution Approach 1:
The patent introduces dynamics by adaptively generating the second quantization table based on the statistical properties (size distribution pattern) of the first quantization table. Rather than using fixed quantization increments, the system dynamically adjusts quantization values according to the actual data characteristics, achieving optimal compression efficiency while minimizing quality loss for the given image content.
Data Source
AI summary
Provided is a re-encoding method including obtaining a first quantization table from a bitstream including an image encoded using the first quantization table; obtaining a second quantization table based on a pattern representing a size distribution of values of elements of the first quantization table, the second quantization table including elements respectively corresponding to the elements of the first quantization table; and re-encoding a reconstructed image by using the second quantization table, the reconstructed image being obtained by decoding the encoded image by using the first quantization table.