Block Data Compression Using Adaptive Bit Shifting
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Solution Overview
Problem
Existing data compression methods, particularly lossy compression, often result in compressed data occupying a large storage space due to variable compression ratios and inefficiencies in handling data with non-uniform probability distributions.
Innovation Solution
A method and apparatus for data compression that calculates the average significant digit value and storage bit width of data blocks, dynamically shifting the remainder part of the data to achieve a fixed compression ratio, thereby reducing storage space while allowing for parallel processing and efficient compression across various data types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If transform domain compression (DCT) is used, then data can be compressed, but the compressed data occupies a large storage space
Solution Approach 1:
The patent changes the compression approach by dynamically adjusting the shift bit width based on the significant digit values of the data block. Instead of using fixed DCT transformation, it applies variable bit-shifting operations where the shift amount is determined by calculating the average significant digit value and comparing it with the target storage bit width. This parameter-based adaptation allows optimal compression for each data block while meeting the storage space requirement.
2Adaptability or versatility
If variable compression ratio is used, then different data can be compressed differently, but the compressed data occupies larger storage space due to overhead
Solution Approach 1:
The patent applies local quality by processing each data block independently with its own calculated shift bit width based on its specific significant digit values. Each block is compressed according to its local characteristics rather than applying a global compression scheme. This allows adaptive compression for different data types while minimizing overhead since only the shift bit width parameter needs to be stored for each block.
3Productivity
If traditional compression algorithms are used, then compression can be achieved, but parallel processing efficiency is reduced
Solution Approach 1:
The patent segments the data into fixed-size blocks and processes each block independently through the compression algorithm. The compression function takes a data block as input and produces a compressed result, allowing multiple blocks to be processed simultaneously in parallel. This segmentation approach enables efficient parallel processing while maintaining relatively simple processing logic for each individual block.
Data Source
AI summary
A data compression method, apparatus, a data decompression method and apparatus are provided. In the methods an apparatuses, on the basis of an average effective bit value of data in a data block and an average storage bit width occupied by e remaining part of each item of data in the compressed data block, compression of a fixed compression rate is implemented on the remaining part of the data, reducing the storage space occupied by the remaining part of the data whilst allowing for quick restoration of the compressed data into the original data.


