Custom Probability Tables for JPEG Compression
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Solution Overview
Problem
JPEG compression using predefined probability tables often results in suboptimal compressed image file sizes due to mismatched image statistics, while custom probability tables require additional resources and computational effort.
Innovation Solution
A method and system that generate custom probability tables based on a representative sample of the image, using iterative refinement to ensure convergence of entropy calculations, allowing for efficient entropy coding with reduced computational and memory requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If custom probability tables are generated for the entire image, then compression ratio is improved, but memory usage and computational resources increase
Solution Approach 1:
The patent divides the image into multiple blocks and generates separate probability tables for each block rather than using a single table for the entire image. This segmentation allows custom probability tables to be created for local regions, improving compression ratio while limiting memory usage to only the statistics needed for each individual block rather than the entire image.
Solution Approach 2:
The patent extracts only the necessary statistical information from each image block to generate probability tables, rather than processing or storing all image data. By taking out only the essential statistics (such as coefficient distributions) needed for entropy coding, the system achieves better compression without requiring proportional increases in memory resources.
2Loss of substance
If custom probability tables are generated for the entire image, then compression ratio is improved, but computational effort increases
Solution Approach 1:
The patent segments the image processing into independent block-level operations, where probability tables are generated for each block separately. This segmentation reduces computational effort by allowing parallel processing of blocks and avoiding the need to compute statistics for the entire image at once, thus improving productivity while maintaining compression benefits.
Solution Approach 2:
The patent applies partial action by generating probability tables for only the necessary blocks or regions rather than processing the entire image uniformly. This selective approach computes statistics only where needed for optimal compression, reducing overall computational resources while still achieving improved compression ratios in the critical regions.
3Productivity
If predefined probability tables are used, then computational resources are reduced, but compression ratio deteriorates
Solution Approach 1:
The patent performs preliminary action by pre-computing statistics for each image block and generating custom probability tables before the actual entropy coding process. This preliminary computation of block-specific statistics enables better compression ratios during encoding, while the pre-computed nature of the tables keeps computational resources manageable during the main processing phase.
Solution Approach 2:
The patent applies local quality by creating probability tables that are specific to each image block's characteristics rather than using a uniform predefined table for the entire image. This local customization of probability tables matches the statistical properties of each region, improving compression ratio by adapting to local variations in image content while keeping computational resources localized to each block.
Data Source
AI summary
An optimized method and system to generate a compressed image utilizing custom probability tables are described. The system may include a input module to receive a digital image, a sample generator to generate a representative sample image from the input image, a custom probability tables generator to generate custom probability tables and an entropy coder to encode the input image utilizing the custom probability tables. The custom probability tables generator may be configured to generate custom probability tables utilizing the representative sample image.