Inpainting by flexible haar-wavelet shrinkage

R. H. CHAN; S. SETZER; G. STEIDL

doi:10.1137/070711499

Inpainting by flexible haar-wavelet shrinkage

R. H. CHAN, S. SETZER, G. STEIDL

Research output: Journal Publications › Journal Article (refereed) › peer-review

23 Citations (Scopus)

Abstract

We present novel wavelet-based inpainting algorithms. Applying ideas from anisotropic regularization and diffusion, our models can better handle degraded pixels at edges. We interpret our algorithms within the framework of forward-backward splitting methods in convex analysis and prove that the conditions for ensuring their convergence are fulfilled. Numerical examples illustrate the good performance of our algorithms.

Original language	English
Pages (from-to)	273-293
Number of pages	21
Journal	SIAM Journal on Imaging Sciences
Volume	1
Issue number	3
DOIs	https://doi.org/10.1137/070711499
Publication status	Published - Jan 2008
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2008 Society for Industrial and Applied Mathematics and by SIAM.

Keywords

Anisotropic methods
Forward-backward algorithm
Image inpainting
Wavelet shrinkage

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10.1137/070711499

Cite this

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AB - We present novel wavelet-based inpainting algorithms. Applying ideas from anisotropic regularization and diffusion, our models can better handle degraded pixels at edges. We interpret our algorithms within the framework of forward-backward splitting methods in convex analysis and prove that the conditions for ensuring their convergence are fulfilled. Numerical examples illustrate the good performance of our algorithms.

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KW - Wavelet shrinkage

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Inpainting by flexible haar-wavelet shrinkage

Abstract

Bibliographical note

Keywords

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