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Proceedings Paper

Geometric Bayesian inpainting and applications
Author(s): Jianhong Shen
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Paper Abstract

Inpainting is an image interpolation problem, with broad applications in image processing and the digital technology. This paper presents our recent efforts in developing inpainting models based on the Bayesian and variational principles. We discuss several geometric image (prior) models, their role in the construction of variational inpainting models, the resulting Euler-Lagrange differential equations, and their numerical implementation.

Paper Details

Date Published: 23 December 2002
PDF: 12 pages
Proc. SPIE 4792, Image Reconstruction from Incomplete Data II, (23 December 2002); doi: 10.1117/12.447889
Show Author Affiliations
Jianhong Shen, Univ. of Minnesota Twin Cities (United States)

Published in SPIE Proceedings Vol. 4792:
Image Reconstruction from Incomplete Data II
Philip J. Bones; Michael A. Fiddy; Rick P. Millane, Editor(s)

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