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A Laplacian based image filtering using switching noise detector

This paper presents a Laplacian-based image filtering method. Using a local noise estimator function in an energy functional minimizing scheme we show that Laplacian that has been known as an edge detection function can be used for noise removal applications. The algorithm can be implemented on a 3x...

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Detalles Bibliográficos
Autores principales: Ranjbaran, Ali, Hassan, Anwar Hasni Abu, Jafarpour, Mahboobe, Ranjbaran, Bahar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4398689/
https://www.ncbi.nlm.nih.gov/pubmed/25897407
http://dx.doi.org/10.1186/s40064-015-0846-5
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author Ranjbaran, Ali
Hassan, Anwar Hasni Abu
Jafarpour, Mahboobe
Ranjbaran, Bahar
author_facet Ranjbaran, Ali
Hassan, Anwar Hasni Abu
Jafarpour, Mahboobe
Ranjbaran, Bahar
author_sort Ranjbaran, Ali
collection PubMed
description This paper presents a Laplacian-based image filtering method. Using a local noise estimator function in an energy functional minimizing scheme we show that Laplacian that has been known as an edge detection function can be used for noise removal applications. The algorithm can be implemented on a 3x3 window and easily tuned by number of iterations. Image denoising is simplified to the reduction of the pixels value with their related Laplacian value weighted by local noise estimator. The only parameter which controls smoothness is the number of iterations. Noise reduction quality of the introduced method is evaluated and compared with some classic algorithms like Wiener and Total Variation based filters for Gaussian noise. And also the method compared with the state-of-the-art method BM3D for some images. The algorithm appears to be easy, fast and comparable with many classic denoising algorithms for Gaussian noise.
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spelling pubmed-43986892015-04-20 A Laplacian based image filtering using switching noise detector Ranjbaran, Ali Hassan, Anwar Hasni Abu Jafarpour, Mahboobe Ranjbaran, Bahar Springerplus Research This paper presents a Laplacian-based image filtering method. Using a local noise estimator function in an energy functional minimizing scheme we show that Laplacian that has been known as an edge detection function can be used for noise removal applications. The algorithm can be implemented on a 3x3 window and easily tuned by number of iterations. Image denoising is simplified to the reduction of the pixels value with their related Laplacian value weighted by local noise estimator. The only parameter which controls smoothness is the number of iterations. Noise reduction quality of the introduced method is evaluated and compared with some classic algorithms like Wiener and Total Variation based filters for Gaussian noise. And also the method compared with the state-of-the-art method BM3D for some images. The algorithm appears to be easy, fast and comparable with many classic denoising algorithms for Gaussian noise. Springer International Publishing 2015-03-08 /pmc/articles/PMC4398689/ /pubmed/25897407 http://dx.doi.org/10.1186/s40064-015-0846-5 Text en © Ranjbaran et al.; licensee Springer. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.
spellingShingle Research
Ranjbaran, Ali
Hassan, Anwar Hasni Abu
Jafarpour, Mahboobe
Ranjbaran, Bahar
A Laplacian based image filtering using switching noise detector
title A Laplacian based image filtering using switching noise detector
title_full A Laplacian based image filtering using switching noise detector
title_fullStr A Laplacian based image filtering using switching noise detector
title_full_unstemmed A Laplacian based image filtering using switching noise detector
title_short A Laplacian based image filtering using switching noise detector
title_sort laplacian based image filtering using switching noise detector
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4398689/
https://www.ncbi.nlm.nih.gov/pubmed/25897407
http://dx.doi.org/10.1186/s40064-015-0846-5
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