Image Compression Apparatus Using Adaptive Region Downsampling
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Solution Overview
Problem
JPEG image compression methods degrade image quality uniformly across all regions, including important and unimportant areas, due to irreversible quantization processing, limiting the ability to achieve high compression rates while maintaining image quality.
Innovation Solution
The method involves downsampling image data into smaller regions, rearranging and inserting fill data to match block sizes, and performing compression processing on these regions, allowing for variable image quality across regions using a general-purpose JPEG compressor and expander.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the quantization table or quantization factor Q is changed to increase the quantization step width for higher compression rate, then the data compression rate is improved, but the image quality is greatly degraded uniformly across all regions
Solution Approach 1:
The patent applies local quality by differentiating image regions into important and unimportant areas, then applying different quantization step widths to each region. Important regions use smaller quantization step widths to preserve quality, while unimportant regions use larger step widths to achieve higher compression. This resolves the contradiction by making compression quality adaptive to regional importance rather than uniform across the entire image.
Solution Approach 2:
The patent segments the image into multiple regions with different importance levels before applying quantization. By dividing the image data into region-specific segments and applying different compression parameters to each segment, the system achieves both high compression rates in unimportant areas and quality preservation in important areas, resolving the uniform quality degradation problem.
2Manufacturing precision
If a mask processing is performed in each block to achieve different image qualities in different regions, then regional quality differentiation is achieved, but the device complexity increases and data amount reduction is limited
Solution Approach 1:
The patent performs preliminary action by pre-classifying image regions into important and unimportant areas before the main quantization process. This preliminary region classification allows subsequent quantization to be applied efficiently without requiring complex per-block mask processing during the main compression flow, thereby reducing device complexity while maintaining regional quality differentiation.
Data Source
AI summary
To improve the data compression ratio in the data compression/decompression method utilizing the down-sampling process. Image data in a DS area division unit (130) is divided into a plenty of DS areas and DS areas which are not important are converted into contracted data of the block size by down-sampling in a down-sampling unit (131). A relocation unit (132) allocates two or more contracted data in one DS area, inserts file data into the other portion in the DS area, and removes the DS area where no contracted data is allocated, thereby reducing the entire image size. The image data thus contracted is inputted into a JPEG encoder (14) and subjected to a DCT process and a quantization process for each block. When performing restoration, decompression is performed by the JPEG decoder and the original location is restored. As for the contracted data, interpolation is performed to restore the image data.