Data Compression Labels Using Frequency-Based Bit Permutations
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Solution Overview
Problem
Current data compression and encryption methods face challenges in achieving optimal compression levels while minimizing computational resources and ensuring efficient decompression, particularly in handling diverse data types and requiring flexible bit length allocation.
Innovation Solution
A method involving the division of data into portions and sub-divisions, followed by frequency analysis and label assignment, where labels represent combined values of sub-division permutations, allowing for adaptive bit length selection and efficient compression, and incorporating headers for decompression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Volume of stationary object
If data is compressed using traditional methods, then storage space is reduced, but computational resources and processing time increase
Solution Approach 1:
The patent divides data into fixed-length portions (e.g., 6-bit portions) and processes each portion independently through frequency analysis and label assignment. This segmentation allows for efficient parallel processing and reduces the computational complexity compared to traditional whole-data compression methods, while achieving significant storage space reduction through compact label representation.
2Volume of stationary object
If compression level is increased, then storage efficiency improves, but decompression speed and processing efficiency decrease
Solution Approach 1:
The patent performs frequency analysis and assigns labels to all possible portion permutations in advance during the compression phase. The label lookup table is pre-computed, so during decompression, the system only needs to perform simple label matching and reconstruction operations. This preliminary action during compression enables extremely fast decompression speed while maintaining high compression ratios.
3Ease of operation
If fixed bit length is used for data representation, then processing simplicity is maintained, but compression efficiency for diverse data types decreases
Solution Approach 1:
The patent applies different label assignments and portion permutations locally based on the specific data characteristics and frequency analysis results for each data type. While maintaining a uniform fixed bit length structure (e.g., 6-bit portions) for processing simplicity, the label mapping is optimized locally for different data types (text, images, audio, video), achieving high compression efficiency across diverse data types without sacrificing processing simplicity.
Data Source
AI summary
A method of compression is disclosed in which an input sequence of bits is divided into a plurality of portions. Each portion is sub-divided into a plurality of sub-divisions. Frequency analysis is performed to determine the number of occurrences of each sub-division permutation and new values are assigned, based on the frequency analysis, to each of the sub-division permutations. For each portion a label representing the permutation of bits in that portion is assigned. The label comprises a representation of a combined value resulting from combining the new values associated with the sub-division permutations of that portion. A processed sequence of bits is generated by replacing, within the input sequence of bits, bit portions with the respective label representing the permutation of bits in that portion.