Image Data Compression with Dynamic LSB Removal
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Solution Overview
Problem
Existing image data compression methods face challenges in balancing compression rate and image quality, with lossless compression not guaranteeing a predictable compression rate and lossy compression often resulting in degraded image quality, making them unsuitable for applications with limited memory resources.
Innovation Solution
A method that dynamically adjusts the compression rate by calculating the accumulated target data size and comparing it with the actual compressed data size, removing least significant bits (LSB) of image blocks when the difference is below a threshold to control the compression rate while maintaining image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If lossless compression is used to maintain image quality, then image quality is preserved, but compression rate cannot be guaranteed and compressed data size becomes unpredictable
Solution Approach 1:
The patent dynamically adjusts the compression strategy for each image block based on real-time feedback. The compression rate control circuit continuously monitors the accumulated compressed data size and compares it with the target data size, then adaptively selects between lossless and lossy compression methods for subsequent blocks, making the compression process dynamic rather than static
Solution Approach 2:
The patent changes the compression parameter (compression rate) by removing a predetermined number of least significant bits (LSBs) from image blocks when the accumulated compressed data size approaches the target. This parameter modification allows transition between lossless and lossy compression states to control the final data size while managing image quality degradation
2Quantity of substance
If lossy compression is used to achieve higher compression rate, then compressed data size is reduced, but image quality deteriorates
Solution Approach 1:
The patent applies different compression quality levels to different image blocks based on their position and the overall compression needs. Early blocks may use lossless compression to maintain quality, while later blocks use lossy compression (LSB removal) to control data size, creating local variations in quality that collectively achieve the target compression rate
Solution Approach 2:
The patent removes a predetermined number of least significant bits (partial action) from image block data to achieve compression. This partial removal of data components provides a controlled amount of lossy compression that balances data size reduction with acceptable image quality degradation
3Device complexity
If compression is performed without controlling the compression rate, then processing is simpler, but applications with limited memory resources cannot be satisfied
Solution Approach 1:
The patent implements a feedback control mechanism where the compression rate control circuit monitors the accumulated compressed data size after each block compression, compares it with the target data size, and uses this feedback information to adjust the compression strategy for subsequent blocks, ensuring the final compressed file meets the memory constraints
Solution Approach 2:
The patent performs preliminary calculations of the target data size and predetermined threshold before compression begins. The compression rate control circuit pre-determines the compression parameters and monitoring thresholds, allowing the compression process to proceed systematically while ensuring the final data size constraint is met
Data Source
AI summary
A method for compressing image data is provided. The image data includes a file to be compressed, which includes N blocks to be compressed. The method includes: setting a target data increment of each of the N blocks of the file according to a 0th accumulated target data size and an Nth accumulated target data size; before compressing an nth block, calculating an (n−1)th accumulated target data size of an (n−1)th block according to the 0th accumulated target data size and the target data increment; when a difference between an (n−1)th accumulated compressed data size and the (n−1)th accumulated target data size is smaller than a predetermined threshold, removing X least significant bit(s) of a plurality of sets of data in the nth block to generate an updated nth block; and compressing the updated nth block to generate a compressed nth block.