Cross-Image Entropy Coding for Lower Image Storage Footprint
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Solution Overview
Problem
Current multimedia compression techniques are inefficient in optimizing storage space for large collections of images and videos, as they are designed to compress content on a per-image basis rather than considering multiple images or videos collectively, leading to storage inefficiencies and increased costs for storage providers.
Innovation Solution
A method and system for compressing multiple images using lossy compression techniques, such as JPEG, which involves generating codewords from pixel blocks, transforming coefficients, quantizing, and entropy encoding, with the generation of an entropy coding table based on the frequency of occurrence of codewords to optimize storage space, allowing for variable-length coding that reduces the bit length as the occurrence increases, thereby compressing images into a lower-storage footprint format.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If per-image compression is used, then each image can be compressed independently, but storage efficiency for multiple images is insufficient
Solution Approach 1:
The patent merges multiple images into a single composite image for compression processing. By combining multiple source images and their corresponding codeword sequences into unified data structures, the system achieves collective compression that improves storage efficiency while managing complexity through structured integration rather than independent processing of each image
2Quantity of substance
If lossy compression is applied to multiple images, then storage space is reduced, but image quality may deteriorate
Solution Approach 1:
The patent applies parameter changes by using variable-length codeword sequences where the bit length dynamically adjusts based on the frequency of occurrence of each codeword across multiple images. Frequently occurring codewords are assigned shorter bit representations, while less frequent ones receive longer representations. This statistical parameter adjustment achieves efficient compression while maintaining acceptable image quality by preserving important visual information
3Productivity
If variable-length coding is used based on codeword frequency, then bit length is reduced for frequent codewords, but entropy coding table generation becomes more complex
Solution Approach 1:
The patent applies preliminary action by pre-analyzing the frequency of occurrence of each codeword across all images before generating the entropy coding table. This statistical analysis is performed in advance to determine the optimal variable-length coding scheme, allowing the system to achieve high compression ratios while managing complexity through upfront planning rather than complex real-time decision-making during compression
Data Source
AI summary
A method for compression across multiple images is provided. The method includes receiving a plurality of images at a storage device. For each image of the plurality of images, the method includes generating codewords using lossy compression, each codeword defined as a bit string. The method further includes generating an entropy coding table based on the codewords generated for each image of the plurality of images and entropy encoding the plurality of images using the generated entropy coding table.