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Proceedings Paper

Image compression using constrained relaxation
Author(s): Zhihai He
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Paper Abstract

In this work, we develop a new data representation framework, called constrained relaxation for image compression. Our basic observation is that an image is not a random 2-D array of pixels. They have to satisfy a set of imaging constraints so as to form a natural image. Therefore, one of the major tasks in image representation and coding is to efficiently encode these imaging constraints. The proposed data representation and image compression method not only achieves more efficient data compression than the state-of-the-art H.264 Intra frame coding, but also provides much more resilience to wireless transmission errors with an internal error-correction capability.

Paper Details

Date Published: 29 January 2007
PDF: 6 pages
Proc. SPIE 6508, Visual Communications and Image Processing 2007, 65082P (29 January 2007); doi: 10.1117/12.705098
Show Author Affiliations
Zhihai He, Univ. of Missouri, Columbia (United States)


Published in SPIE Proceedings Vol. 6508:
Visual Communications and Image Processing 2007
Chang Wen Chen; Dan Schonfeld; Jiebo Luo, Editor(s)

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