JPEG Multi-Block Recompression for Lossless Random Access
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Solution Overview
Problem
Current image compression algorithms, such as JPEG, struggle to further compress already compressed image files due to bit-to-bit compatibility and progressive storage mode limitations, making it difficult to achieve additional compression ratios without introducing noticeable artifacts or degrading image quality.
Innovation Solution
The proposed solution involves separating previously compressed data streams into input blocks, using block-image synchronization information to recompress and decompress data, and applying predictive models to maintain bit-to-bit compatibility while increasing compression ratios, allowing for real-time multi-block lossless recompression and random access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If universal compression algorithms like Deflate, ZLIB, or LZ are applied to JPEG compressed files, then the compression process is simple and fast, but no further compression ratio is achieved
Solution Approach 1:
The patent segments the JPEG compressed file into multiple blocks, where each block contains a header and image data. This segmentation allows the system to process and recompress specific portions of the file independently, enabling further compression by identifying and eliminating redundancies across block boundaries that universal algorithms miss.
Solution Approach 2:
The patent changes the compression parameters by applying a second compression algorithm specifically tuned for the segmented block structure of JPEG files. This involves modifying how compression is applied at the block level versus the traditional file-level approach, allowing for improved compression ratios without sacrificing speed.
2Reliability
If lossless recompression is applied to already compressed JPEG files, then image quality is maintained, but the compression ratio improvement is limited
Solution Approach 1:
The patent performs preliminary decomposition of the JPEG file into standardized blocks with headers before applying the second compression algorithm. This preliminary action prepares the data structure to reveal hidden redundancies that can be exploited for further lossless compression while maintaining image quality.
Solution Approach 2:
The patent introduces an intermediary processing stage that acts on the segmented blocks between the original JPEG compression and the final compressed output. This intermediary stage applies block-level analysis and compression techniques that bridge the gap between maintaining quality and achieving higher compression ratios.
3Quantity of substance
If the entire JPEG file is decompressed and recompressed as a single unit, then maximum compression ratio is achieved, but processing time increases significantly
Solution Approach 1:
The patent divides the JPEG file into multiple independent blocks that can be processed in parallel or sequentially with minimal overhead. This segmentation enables the system to achieve near-maximum compression ratios without the computational burden of processing the entire file as one unit, significantly reducing processing time.
Solution Approach 2:
The patent applies compression algorithms partially to each block rather than excessively processing the entire file. By focusing compression efforts on individual blocks with appropriate algorithms, the system achieves sufficient compression ratios without the exponential increase in processing time that would result from full-file processing.
4Productivity
If block-image synchronization information is used for random access, then processing efficiency is improved, but system complexity increases
Solution Approach 1:
The patent organizes JPEG data into standardized blocks with synchronized headers that contain metadata about each block's content and compression characteristics. This segmentation with synchronization information enables efficient random access to specific blocks without requiring complex navigation structures, improving processing efficiency while maintaining manageable system complexity.
Data Source
AI summary
Exemplary methods, computer systems, and computer program products for processing a previously compressed data stream in a computer environment are provided. In one embodiment, the computer environment is configured for separating a previously compressed data stream into an input data block including a header input block having a previously compressed header. Sequences of bits are included with the input data block. Compression scheme information is derived from the previously compressed header. The input data block is accessed and recompressed following the header input block in the previously compressed data stream one at a time using block-image synchronization information. Access to the block-image synchronization information is initialized by the compression scheme information to generate an output data block. The block-image synchronization information is used to provide decompression information to facilitate decompression of the results of the output data block.