Adaptive Data Compression via Edge Detection and Thinning
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Solution Overview
Problem
Current data compression systems for Continuous Tone (CT) data are inefficient, particularly due to high processing time and deterioration of system performance, despite being high in compressibility, whereas reversible compression systems like PackBits are not suitable for all data types.
Innovation Solution
A data compression apparatus that employs a combination of thinning processing, reversible and non-reversible compression techniques, edge detection, and differential coding to optimize bit representation, allowing for efficient compression of CT data by adapting bit lengths based on image features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If non-reversible compression processing is applied to CT data, then compressibility is improved, but processing time increases and system performance deteriorates
Solution Approach 1:
The patent segments the image data into edge portions and non-edge portions through edge detection, and applies different compression methods to each segment. Edge portions use reversible compression to maintain quality, while non-edge portions use non-reversible compression for high compression ratio, thus resolving the contradiction between compressibility and processing time
Solution Approach 2:
The patent applies different compression qualities to different regions of the image based on edge detection results. Areas with edges maintain higher quality through reversible compression, while smooth areas accept lower quality for better compression, optimizing the balance between compressibility and processing time
2Manufacturing precision
If reversible compression processing is applied to all data, then image quality is maintained, but compressibility decreases
Solution Approach 1:
The patent segments the image into edge and non-edge portions, applying reversible compression only to edge portions where quality is critical, while applying non-reversible compression to non-edge portions where compressibility is prioritized, thus achieving both quality maintenance and high compressibility
Solution Approach 2:
Different compression qualities are applied locally to different image regions based on edge detection, with higher quality for edge regions and higher compression for non-edge regions, optimizing the overall balance between image quality and compressibility
3Reliability
If conventional compression methods are used, then system performance is maintained, but processing speed decreases
Solution Approach 1:
The patent segments the compression process into two parallel paths based on edge detection results, allowing simultaneous processing of different image regions with appropriate compression methods, thus improving processing speed while maintaining system performance
Solution Approach 2:
The patent dynamically selects compression methods based on edge detection results, switching between reversible and non-reversible compression strategies according to the specific characteristics of each image region, optimizing processing speed for each local area
Data Source
AI summary
A data compression apparatus includes a thinning section that thins numerical values from a succession of values constituting compressed data to create first and second compressed data; a reversible compression section for the first compressed data; a detecting section that detects an edge portion of the image; and a non-reversible compression section that processes the second compressed data based on a result of the edge detection. When the detecting section detects no edge portion, the non-reversible compression section outputs a predetermined code of a number of bits. When the detecting section detects the edge portion, the non-reversible compression section outputs a first value based on image numerical value when involved with a predetermined positional relation expressed by a first number of bits and a second value expressed by a few number of bits than the first number when the image numerical value is not involved with a predetermined positional relation.