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L2 Optimized Predictive Image Coding with L∞ Bound

<p>In many scientific, medical and defense applications of image/video compression, an <em>l</em><sub>∞ </sub>error bound is required. However, pure <em>l</em><sub>∞</sub>-optimized image coding, colloquially known as near-lossless image coding, is prone to structured errors such as contours and speckles if the bit rate is not sufficiently high; moreover, previous <em>l</em><sub>∞</sub>-based image coding methods suffer from poor rate control. In contrast, the <em>l</em><sub>2</sub> error metric aims for average fidelity and hence preserves the subtlety of smooth waveforms better than the <em>l</em><sub>∞</sub> error metric and it offers fine granularity in rate control; but pure <em>l</em><sub>2</sub>-based image coding methods (e.g., JPEG 2000) cannot bound individual errors as <em>l</em><sub>∞</sub>-based methods can. This thesis presents a new compression approach to retain the benefits and circumvent the pitfalls of the two error metrics.</p> / Master of Applied Science (MASc)

Identiferoai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/12744
Date04 1900
CreatorsChuah, Sceuchin
ContributorsWu, Xiaolin, Electrical and Computer Engineering
Source SetsMcMaster University
Detected LanguageEnglish
Typethesis

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