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Proceedings Paper

Functional minimization problems in image processing
Author(s): Yunho Kim; Luminita A. Vese
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Paper Abstract

In this work we wish to recover an unknown image from a blurry version. We solve this inverse problem by energy minimization and regularization. We seek a solution of the form u + v, where u is a function of bounded variation (cartoon component), while v is an oscillatory component (texture), modeled by a Sobolev function with negative degree of differentiability. Experimental results show that this cartoon + texture model better recovers textured details in natural images, by comparison with the more standard models where the unknown is restricted only to the space of functions of bounded variation.

Paper Details

Date Published: 26 February 2008
PDF: 11 pages
Proc. SPIE 6814, Computational Imaging VI, 68140Q (26 February 2008); doi: 10.1117/12.775699
Show Author Affiliations
Yunho Kim, Univ. of California, Los Angeles (United States)
Luminita A. Vese, Univ. of California, Los Angeles (United States)

Published in SPIE Proceedings Vol. 6814:
Computational Imaging VI
Charles A. Bouman; Eric L. Miller; Ilya Pollak, Editor(s)

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