Geometric Bayesian inpainting and applications

Jianhong Shen

doi:10.1117/12.447889

23 December 2002 Geometric Bayesian Inpainting and Applications

Jianhong Shen

Proceedings Volume 4792, Image Reconstruction from Incomplete Data II; (2002) https://doi.org/10.1117/12.447889
Event: International Symposium on Optical Science and Technology, 2002, Seattle, WA, United States

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.

Citation Download Citation

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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