Command Byte Pathway Encoding for Lossless Data Compression
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Solution Overview
Problem
Current data compression methods, particularly lossless ones, face challenges in efficiently reducing data size while maintaining data integrity, especially for large files like digital images, where repetitive patterns are not always easily identifiable.
Innovation Solution
The method involves creating reproducible arrays of byte values and identifying contiguous pathways within these arrays to encode data patterns as command byte values, allowing for lossless compression by translating between original byte sets and pathway representations, which are then further compressed using secondary arrays with tailored frequency distributions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If lossless compression methods are used to maintain data integrity, then data fidelity is preserved, but compression ratio is limited due to lack of repetitive patterns
Solution Approach 1:
The patent transforms the data representation parameters by converting byte values into pathway descriptions within reproducible arrays. This parameter transformation enables compression of data that lacks traditional repetitive patterns, as the pathway representation captures spatial and sequential relationships that reduce entropy without losing information.
Solution Approach 2:
The patent introduces a new dimensional approach by mapping data into multi-dimensional reproducible arrays and encoding pathways through these structures. This dimensional transformation allows the compression algorithm to exploit spatial relationships and patterns that are not apparent in traditional linear data representations, thereby achieving better compression ratios while maintaining lossless fidelity.
2Quantity of substance
If traditional compression algorithms are applied to large files, then some compression is achieved, but processing time increases significantly
Solution Approach 1:
The patent employs preliminary action by pre-generating reproducible arrays that contain structured patterns and relationships. These arrays are created in advance and can be reused during the compression process, eliminating the need for complex real-time analysis of large datasets. This pre-computation approach significantly reduces processing time while maintaining effective compression ratios.
3Volume of stationary object
If data is compressed to reduce file size, then storage efficiency improves, but transmission time may increase due to compression overhead
Solution Approach 1:
The patent replaces traditional mechanical compression mechanisms with a mathematical transformation approach based on pathway encoding in reproducible arrays. This substitution eliminates the need for iterative searching and pattern matching that characterize traditional compression algorithms, thereby reducing computational overhead and transmission preparation time while achieving efficient size reduction.
Data Source
AI summary
A method implemented in a computer system may include reading a first set of data byte values, providing a reproducible first array that includes at least one of each data byte value in the first set, identifying in the first array a first contiguous pathway that defines a set of data byte values matching the first set, and creating a second set of command byte values representing the first contiguous pathway. The method may further include providing a reproducible second array that includes at least one of each command byte value in the second set, identifying in the second array a second contiguous pathway that defines a set of command byte values matching the second set, and creating a third set of command byte values representing the second contiguous pathway.