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Proceedings Paper

Fast texture and structure image reconstruction using the perceptual hash
Author(s): V. V. Voronin; V. I. Marchuk; V. A. Frantc; Karen Egiazarian
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Paper Abstract

This paper focuses on the fast texture and structure reconstruction of images. The proposed method, applied to images, consists of several steps. The first one deals with the extracted textural features of the input images based on the Law’s energy. The pixels around damaged image regions are clustered using these features, that allow to define the correspondence between pixels from different patches. Second, cubic spline curve is applied to reconstruct a structure and to connect edges and contours in the damaged area. The choice of the current pixel to be recovered is decided using the fast marching approach. The Telea method or modifications of the exemplar based method are used after this depending on the classification of the regions where to-be-restored pixel is located. In modification to quickly find patches we use the perceptual hash. Such a strategy allows to get some data structure containing the hashes of similar patches. This enables us to reduce the search procedure to the procedure for "calculations" of the patch. The proposed method is tested on various samples of images, with different geometrical features and compared with the state-of-the-art image inpainting methods; the proposed technique is shown to produce better results in reconstruction of missing small and large objects on test images.

Paper Details

Date Published: 19 February 2013
PDF: 12 pages
Proc. SPIE 8655, Image Processing: Algorithms and Systems XI, 86550R (19 February 2013); doi: 10.1117/12.2002829
Show Author Affiliations
V. V. Voronin, Don State Technical Univ. (Russian Federation)
V. I. Marchuk, Don State Technical Univ. (Russian Federation)
V. A. Frantc, Don State Technical Univ. (Russian Federation)
Karen Egiazarian, Tampere Univ. of Technology (Finland)


Published in SPIE Proceedings Vol. 8655:
Image Processing: Algorithms and Systems XI
Karen O. Egiazarian; Sos S. Agaian; Atanas P. Gotchev, Editor(s)

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