Hybrid Image Data Compression System with Code Selection Circuit
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Solution Overview
Problem
Existing image data compression methods face challenges in maintaining image quality while efficiently compressing data, particularly in block-based compression, which often results in increased memory requirements and degradation when random access is supported.
Innovation Solution
A hybrid image data processing system that selectively uses lossy and lossless compression methods, employing a code selection circuit to choose between compressed codes based on their size and merit, ensuring efficient compression without significant image quality degradation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If block-based compression is used to reduce memory usage, then memory capacity requirements decrease, but image quality degrades and compression fails when compressed data exceeds block buffer space
Solution Approach 1:
The image frame is divided into multiple blocks, and each block is compressed independently using lossless compression. This segmentation allows random access to individual blocks while maintaining image quality, as each block can be processed and stored separately without affecting other blocks.
Solution Approach 2:
The invention changes the compression approach from traditional lossy block-based compression to lossless compression. By changing the compression parameter from lossy to lossless, the system maintains exact image quality while still achieving compression through efficient encoding of block data.
2Manufacturing precision
If lossless compression is used to maintain image quality, then image quality is preserved, but compressed data size increases and memory usage increases
Solution Approach 1:
By dividing the image into smaller blocks and compressing each block independently using lossless compression, the system achieves better compression ratios overall. The segmentation allows the lossless compression algorithm to work more efficiently on smaller, manageable units rather than trying to compress the entire image at once.
Solution Approach 2:
The system applies lossless compression selectively to only the necessary portions of the image data that require preservation, rather than applying heavy compression to the entire image. This partial action approach maintains quality where needed while optimizing overall storage efficiency.
3Quantity of substance
If traditional compression methods are used to reduce compressed data size, then memory usage decreases, but compression fails when the size of compressed image data exceeds the size of compression space for each block
Solution Approach 1:
The image is divided into multiple smaller blocks, and each block is compressed independently using lossless compression. This segmentation ensures that the compressed data for each block fits within the allocated buffer space, preventing compression failures while maintaining the ability to handle the entire image.
Data Source
AI summary
An image data compression system, for compressing a frame represented as a plurality of blocks, can include: a lossless compression unit to receive the plurality of blocks and to perform lossless compression thereon resulting in a first code; a lossy compression unit to receive the plurality of blocks and to perform lossy compression thereon resulting in a second code; and a code selection circuit to selectively output one of the first and second codes based upon a figure of merit evaluated for at least one of the first and second codes.