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

Kwok Po NG*, Fan Wang, Xiaoming YUAN

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 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 languageEnglish
Pages (from-to)259-286
Number of pages28
JournalMultidimensional Systems and Signal Processing
Volume22
Issue number1-3
DOIs
Publication statusPublished - 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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