Wrap-Around Wavelet Compression with Selective Bit Retention
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Solution Overview
Problem
Current data compression techniques, particularly for image data, face challenges in achieving high compression ratios without significant loss of image quality, especially when using wrap-around wavelet compression, where reducing precision can introduce substantial color differences and existing lossless compression methods may not meet bandwidth and storage requirements, especially at high resolutions like 8k video.
Innovation Solution
A lossy data compression method using wrap-around wavelet compression that divides each data value into two parts, compressing the most significant bits using wavelet compression and selectively appending bits from the least significant parts to achieve a target compression ratio, while maintaining image quality by progressively improving compression until lossless results are obtained.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If lossless compression methods are used, then image quality is maintained, but compression ratio is insufficient to meet bandwidth and storage requirements
Solution Approach 1:
The patent segments each pixel value into two distinct parts: most significant bits (MSBs) and least significant bits (LSBs). The MSBs are compressed using wrap-around wavelet compression to achieve high compression ratios, while the LSBs are selectively retained and appended to maintain image quality. This segmentation allows the system to achieve both high compression ratios and acceptable image quality simultaneously, resolving the contradiction between compression ratio and image quality.
2Quantity of substance
If wrap-around wavelet compression is applied to reduce precision, then compression ratio increases, but substantial color differences are introduced
Solution Approach 1:
The patent applies different quality requirements to different parts of the data. The most significant bits, which have the greatest impact on color accuracy, are compressed using wrap-around wavelet compression. The least significant bits, which have minimal impact on perceived image quality, are selectively retained and appended to the compressed MSBs. This local quality approach allows aggressive compression of the MSBs while maintaining sufficient color accuracy through the selective retention of LSBs, resolving the contradiction between compression ratio and color accuracy.
3Speed
If memory bandwidth is increased to handle high-resolution data, then data transfer capability improves, but power consumption increases significantly
Solution Approach 1:
The patent changes the parameter of data representation by applying wrap-around wavelet compression to the most significant bits of pixel values. This transformation reduces the number of bits required to represent the same visual information, thereby reducing the memory bandwidth required to transfer high-resolution image data. By modifying the data representation parameters rather than increasing physical bandwidth resources, the system achieves high data transfer capability while avoiding the associated increase in power consumption.
Data Source
AI summary
A lossy method of compressing data, such as image data, which uses wrap-around wavelet compression is described. Each data value is divided into two parts and the first parts, which comprise the most significant bits from the data values, are compressed using wrap-around wavelet compression. Depending upon the target compression ratio and the compression ratio achieved by compressing just the first parts, none, one or more bits from the second parts, or from a data value derived from the second parts, may be appended to the compressed first parts. The method described may be lossy or may be lossless. A corresponding decompression method is also described.