Bounding Lossy Compression using Lossless Codes at Reduced Precision
John Scoville

TL;DR
This paper introduces a novel method for bounding lossy data compression by using lossless codes at reduced precision to establish absolute bounds, improving understanding of compression limits.
Contribution
It presents a new approach that uses lossless codes at reduced precision to set bounds on arbitrary lossy compression algorithms, differing from previous methods.
Findings
Provides a theoretical framework for bounding lossy compression
Establishes absolute bounds that constrain lossy algorithms
Offers insights into the limits of lossy data compression
Abstract
An alternative approach to two-part 'critical compression' is presented. Whereas previous results were based on summing a lossless code at reduced precision with a lossy-compressed error or noise term, the present approach uses a similar lossless code at reduced precision to establish absolute bounds which constrain an arbitrary lossy data compression algorithm applied to the original data.
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Taxonomy
TopicsAlgorithms and Data Compression · Computability, Logic, AI Algorithms · Numerical Methods and Algorithms
