Paper
19 February 2013 Fast texture and structure image reconstruction using the perceptual hash
Author Affiliations +
Proceedings Volume 8655, Image Processing: Algorithms and Systems XI; 86550R (2013) https://doi.org/10.1117/12.2002829
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States
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.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
V. V. Voronin, V. I. Marchuk, V. A. Frantc, and Karen Egiazarian "Fast texture and structure image reconstruction using the perceptual hash", Proc. SPIE 8655, Image Processing: Algorithms and Systems XI, 86550R (19 February 2013); https://doi.org/10.1117/12.2002829
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KEYWORDS
Image restoration

Reconstruction algorithms

Systems modeling

Visual process modeling

Electron beam melting

Image processing

Image segmentation

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