A framelet-based image inpainting algorithm

Jian Feng CAI; Raymond H. CHAN; Zuowei SHEN

doi:10.1016/j.acha.2007.10.002

A framelet-based image inpainting algorithm

Jian Feng CAI^*, Raymond H. CHAN, Zuowei SHEN

^*Corresponding author for this work

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

294 Citations (Scopus)

Abstract

Image inpainting is a fundamental problem in image processing and has many applications. Motivated by the recent tight frame based methods on image restoration in either the image or the transform domain, we propose an iterative tight frame algorithm for image inpainting. We consider the convergence of this framelet-based algorithm by interpreting it as an iteration for minimizing a special functional. The proof of the convergence is under the framework of convex analysis and optimization theory. We also discuss the relationship of our method with other wavelet-based methods. Numerical experiments are given to illustrate the performance of the proposed algorithm.

Original language	English
Pages (from-to)	131-149
Number of pages	19
Journal	Applied and Computational Harmonic Analysis
Volume	24
Issue number	2
DOIs	https://doi.org/10.1016/j.acha.2007.10.002
Publication status	Published - Mar 2008
Externally published	Yes

Funding

This work was supported by HKRGC Grant CUHK 400405 and CUHK DAG 2060257. 3 This work was partially supported by Grant R-146-000-060-112 at the National University of Singapore.

Keywords

Convex analysis
Inpainting
Tight frame

Access to Document

10.1016/j.acha.2007.10.002

Cite this

@article{4f61aadeb27b4b73b294465e263ce95e,

title = "A framelet-based image inpainting algorithm",

abstract = "Image inpainting is a fundamental problem in image processing and has many applications. Motivated by the recent tight frame based methods on image restoration in either the image or the transform domain, we propose an iterative tight frame algorithm for image inpainting. We consider the convergence of this framelet-based algorithm by interpreting it as an iteration for minimizing a special functional. The proof of the convergence is under the framework of convex analysis and optimization theory. We also discuss the relationship of our method with other wavelet-based methods. Numerical experiments are given to illustrate the performance of the proposed algorithm.",

keywords = "Convex analysis, Inpainting, Tight frame",

author = "CAI, {Jian Feng} and CHAN, {Raymond H.} and Zuowei SHEN",

year = "2008",

month = mar,

doi = "10.1016/j.acha.2007.10.002",

language = "English",

volume = "24",

pages = "131--149",

journal = "Applied and Computational Harmonic Analysis",

issn = "1063-5203",

publisher = "Academic Press Inc.",

number = "2",

}

TY - JOUR

T1 - A framelet-based image inpainting algorithm

AU - CAI, Jian Feng

AU - CHAN, Raymond H.

AU - SHEN, Zuowei

PY - 2008/3

Y1 - 2008/3

N2 - Image inpainting is a fundamental problem in image processing and has many applications. Motivated by the recent tight frame based methods on image restoration in either the image or the transform domain, we propose an iterative tight frame algorithm for image inpainting. We consider the convergence of this framelet-based algorithm by interpreting it as an iteration for minimizing a special functional. The proof of the convergence is under the framework of convex analysis and optimization theory. We also discuss the relationship of our method with other wavelet-based methods. Numerical experiments are given to illustrate the performance of the proposed algorithm.

AB - Image inpainting is a fundamental problem in image processing and has many applications. Motivated by the recent tight frame based methods on image restoration in either the image or the transform domain, we propose an iterative tight frame algorithm for image inpainting. We consider the convergence of this framelet-based algorithm by interpreting it as an iteration for minimizing a special functional. The proof of the convergence is under the framework of convex analysis and optimization theory. We also discuss the relationship of our method with other wavelet-based methods. Numerical experiments are given to illustrate the performance of the proposed algorithm.

KW - Convex analysis

KW - Inpainting

KW - Tight frame

UR - http://www.scopus.com/inward/record.url?scp=38949172340&partnerID=8YFLogxK

U2 - 10.1016/j.acha.2007.10.002

DO - 10.1016/j.acha.2007.10.002

M3 - Journal Article (refereed)

AN - SCOPUS:38949172340

SN - 1063-5203

VL - 24

SP - 131

EP - 149

JO - Applied and Computational Harmonic Analysis

JF - Applied and Computational Harmonic Analysis

IS - 2

ER -

A framelet-based image inpainting algorithm

Abstract

Funding

Keywords

Access to Document

Other files and links

Fingerprint

Cite this