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23 December 2002 Geometric Bayesian Inpainting and Applications
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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.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jianhong Shen "Geometric Bayesian Inpainting and Applications", Proc. SPIE 4792, Image Reconstruction from Incomplete Data II, (23 December 2002); https://doi.org/10.1117/12.447889
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