EURASIP Journal on Applied Signal Processing
Volume 2005 (2005), Issue 17, Pages 2758-2771
doi:10.1155/ASP.2005.2758

Constrained Texture Restoration

A. Rareş,1,2 M. J. T. Reinders,1 and J. Biemond1

1Information and Communication Theory Group, Mediamatics Department, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft 2628 CD, The Netherlands
2Division of Image Processing, Radiology Department, Leiden University Medical Center, Leiden 2333 ZA, The Netherlands

Received 11 December 2004; Revised 19 May 2005

Academic Editor: Mauro Barni

Copyright © 2005 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A method is proposed for filling in missing areas of degraded images through explicit structure reconstruction, followed by texture synthesis. The structure being reconstructed represents meaningful edges from the image, which are traced inside the artefact. The structure reconstruction step relies on different properties of the edges touching the artefact and of the areas between them, in order to sketch the missing edges within the artefact area. The texture synthesis step is based on Markov random fields and is constrained by the traced edges in order to preserve both the shape and the appearance of the various regions in the image. The novelty of our contribution concerns constraining the texture synthesis, which proves to give results superior to the original texture synthesis alone, or to the smoothness-preserving structure-based restoration.