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Entropy Constrained Exemplar-based Image Inpainting

Vantigodi, Suraj and Babu, Venkatesh R (2014) Entropy Constrained Exemplar-based Image Inpainting. In: International Conference on Signal Processing and Communications (SPCOM), JUL 22-25, 2014, Banaglore, INDIA.

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Abstract

Image inpainting is the process of filling the unwanted region in an image marked by the user. It is used for restoring old paintings and photographs, removal of red eyes from pictures, etc. In this paper, we propose an efficient inpainting algorithm which takes care of false edge propagation. We use the classical exemplar based technique to find out the priority term for each patch. To ensure that the edge content of the nearest neighbor patch found by minimizing L-2 distance between patches, we impose an additional constraint that the entropy of the patches be similar. Entropy of the patch acts as a good measure of edge content. Additionally, we fill the image by considering overlapping patches to ensure smoothness in the output. We use structural similarity index as the measure of similarity between ground truth and inpainted image. The results of the proposed approach on a number of examples on real and synthetic images show the effectiveness of our algorithm in removing objects and thin scratches or text written on image. It is also shown that the proposed approach is robust to the shape of the manually selected target. Our results compare favorably to those obtained by existing techniques

Item Type: Conference Proceedings
Additional Information: Copy right for this article belongs to the IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Department/Centre: Division of Information Sciences > Supercomputer Education & Research Centre
Depositing User: Id for Latest eprints
Date Deposited: 30 Dec 2015 06:08
Last Modified: 30 Dec 2015 06:08
URI: http://eprints.iisc.ac.in/id/eprint/52984

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