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Image Inpainting Methods Evaluation and Improvement

With the upgrowing of digital processing of images and film archiving, the need for assisted or unsupervised restoration required the development of a series of methods and techniques. Among them, image inpainting is maybe the most impressive and useful. Based on partial derivative equations or text...

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Detalles Bibliográficos
Autores principales: Vreja, Raluca, Brad, Remus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4127254/
https://www.ncbi.nlm.nih.gov/pubmed/25136700
http://dx.doi.org/10.1155/2014/937845
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author Vreja, Raluca
Brad, Remus
author_facet Vreja, Raluca
Brad, Remus
author_sort Vreja, Raluca
collection PubMed
description With the upgrowing of digital processing of images and film archiving, the need for assisted or unsupervised restoration required the development of a series of methods and techniques. Among them, image inpainting is maybe the most impressive and useful. Based on partial derivative equations or texture synthesis, many other hybrid techniques have been proposed recently. The need for an analytical comparison, beside the visual one, urged us to perform the studies shown in the present paper. Starting with an overview of the domain, an evaluation of the five methods was performed using a common benchmark and measuring the PSNR. Conclusions regarding the performance of the investigated algorithms have been presented, categorizing them in function of the restored image structure. Based on these experiments, we have proposed an adaptation of Oliveira's and Hadhoud's algorithms, which are performing well on images with natural defects.
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spelling pubmed-41272542014-08-18 Image Inpainting Methods Evaluation and Improvement Vreja, Raluca Brad, Remus ScientificWorldJournal Review Article With the upgrowing of digital processing of images and film archiving, the need for assisted or unsupervised restoration required the development of a series of methods and techniques. Among them, image inpainting is maybe the most impressive and useful. Based on partial derivative equations or texture synthesis, many other hybrid techniques have been proposed recently. The need for an analytical comparison, beside the visual one, urged us to perform the studies shown in the present paper. Starting with an overview of the domain, an evaluation of the five methods was performed using a common benchmark and measuring the PSNR. Conclusions regarding the performance of the investigated algorithms have been presented, categorizing them in function of the restored image structure. Based on these experiments, we have proposed an adaptation of Oliveira's and Hadhoud's algorithms, which are performing well on images with natural defects. Hindawi Publishing Corporation 2014 2014-07-17 /pmc/articles/PMC4127254/ /pubmed/25136700 http://dx.doi.org/10.1155/2014/937845 Text en Copyright © 2014 R. Vreja and R. Brad. https://creativecommons.org/licenses/by/3.0/ 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.
spellingShingle Review Article
Vreja, Raluca
Brad, Remus
Image Inpainting Methods Evaluation and Improvement
title Image Inpainting Methods Evaluation and Improvement
title_full Image Inpainting Methods Evaluation and Improvement
title_fullStr Image Inpainting Methods Evaluation and Improvement
title_full_unstemmed Image Inpainting Methods Evaluation and Improvement
title_short Image Inpainting Methods Evaluation and Improvement
title_sort image inpainting methods evaluation and improvement
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4127254/
https://www.ncbi.nlm.nih.gov/pubmed/25136700
http://dx.doi.org/10.1155/2014/937845
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