Fast minimization methods for solving constrained total-variation superresolution image reconstruction

Michael Ng; Fan Wang; Xiao Ming Yuan

doi:10.1007/s11045-010-0137-9

Fast minimization methods for solving constrained total-variation superresolution image reconstruction

Michael Ng^*, Fan Wang, Xiao Ming Yuan

^*Corresponding author for this work

Department of Mathematics

Research output: Contribution to journal › Journal article › peer-review

12 Citations (Scopus)

Abstract

In this paper, we study the problem of reconstructing a high-resolution image from several decimated, blurred and noisy low-resolution versions of the high-resolution image. The problem can be formulated as a combination of the total variation (TV) inpainting model and the superresolution image reconstruction model. The main purpose of this paper is to develop an inexact alternating direction method for solving such constrained TV image reconstruction problem. Experimental results are given to show that the proposed algorithm is effective and efficient.

Original language	English
Pages (from-to)	259-286
Number of pages	28
Journal	Multidimensional Systems and Signal Processing
Volume	22
Issue number	1-3
DOIs	https://doi.org/10.1007/s11045-010-0137-9
Publication status	Published - Mar 2011

Scopus Subject Areas

Software
Signal Processing
Information Systems
Hardware and Architecture
Computer Science Applications
Artificial Intelligence
Applied Mathematics

User-Defined Keywords

Alternating direction methods
Constrained total-variation
Inexact computation
Superresolution image reconstruction

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10.1007/s11045-010-0137-9

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title = "Fast minimization methods for solving constrained total-variation superresolution image reconstruction",

abstract = "In this paper, we study the problem of reconstructing a high-resolution image from several decimated, blurred and noisy low-resolution versions of the high-resolution image. The problem can be formulated as a combination of the total variation (TV) inpainting model and the superresolution image reconstruction model. The main purpose of this paper is to develop an inexact alternating direction method for solving such constrained TV image reconstruction problem. Experimental results are given to show that the proposed algorithm is effective and efficient.",

keywords = "Alternating direction methods, Constrained total-variation, Inexact computation, Superresolution image reconstruction",

author = "Michael Ng and Fan Wang and Yuan, {Xiao Ming}",

note = "Funding Information: Acknowledgments Research supported in part by HKRGC grants and HKBU FRGs. Michael Ng would like to dedicate this paper to Professor Nirmal Bose for his guidance and encouragement for Michael{\textquoteright}s research career. Research supported in part by an HKRGC grant and NSFC grant 10701055.",

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doi = "10.1007/s11045-010-0137-9",

language = "English",

volume = "22",

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T1 - Fast minimization methods for solving constrained total-variation superresolution image reconstruction

AU - Ng, Michael

AU - Wang, Fan

AU - Yuan, Xiao Ming

N1 - Funding Information: Acknowledgments Research supported in part by HKRGC grants and HKBU FRGs. Michael Ng would like to dedicate this paper to Professor Nirmal Bose for his guidance and encouragement for Michael’s research career. Research supported in part by an HKRGC grant and NSFC grant 10701055.

PY - 2011/3

Y1 - 2011/3

N2 - In this paper, we study the problem of reconstructing a high-resolution image from several decimated, blurred and noisy low-resolution versions of the high-resolution image. The problem can be formulated as a combination of the total variation (TV) inpainting model and the superresolution image reconstruction model. The main purpose of this paper is to develop an inexact alternating direction method for solving such constrained TV image reconstruction problem. Experimental results are given to show that the proposed algorithm is effective and efficient.

AB - In this paper, we study the problem of reconstructing a high-resolution image from several decimated, blurred and noisy low-resolution versions of the high-resolution image. The problem can be formulated as a combination of the total variation (TV) inpainting model and the superresolution image reconstruction model. The main purpose of this paper is to develop an inexact alternating direction method for solving such constrained TV image reconstruction problem. Experimental results are given to show that the proposed algorithm is effective and efficient.

KW - Alternating direction methods

KW - Constrained total-variation

KW - Inexact computation

KW - Superresolution image reconstruction

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DO - 10.1007/s11045-010-0137-9

M3 - Journal article

AN - SCOPUS:79751536945

SN - 0923-6082

VL - 22

SP - 259

EP - 286

JO - Multidimensional Systems and Signal Processing

JF - Multidimensional Systems and Signal Processing

IS - 1-3

ER -

Fast minimization methods for solving constrained total-variation superresolution image reconstruction

Abstract

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