An Improved Adaptive Weighted Mean Filtering Approach for Metallographic Image Processing

As noise brings great error in the analysis of metallographic images, an adaptive weighted mean filtering method proposed to overcome the shortcomings of the standard mean filtering method.

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Bibliographic Details
Main Authors:	Shao Chonglei, Kaur Preet, Kumar Rajeev
Format:	article
Language:	EN
Published:	De Gruyter 2021
Subjects:	metallographic image adaptive weighted mean filtering average filtering median filtering Science Q Electronic computers. Computer science QA75.5-76.95
Online Access:	https://doaj.org/article/721eb0b503a84d3a9cc482bded6fc035
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id	oai:doaj.org-article:721eb0b503a84d3a9cc482bded6fc035
record_format	dspace
spelling	oai:doaj.org-article:721eb0b503a84d3a9cc482bded6fc0352021-12-05T14:10:51ZAn Improved Adaptive Weighted Mean Filtering Approach for Metallographic Image Processing0334-18602191-026X10.1515/jisys-2020-0080https://doaj.org/article/721eb0b503a84d3a9cc482bded6fc0352021-01-01T00:00:00Zhttps://doi.org/10.1515/jisys-2020-0080https://doaj.org/toc/0334-1860https://doaj.org/toc/2191-026XAs noise brings great error in the analysis of metallographic images, an adaptive weighted mean filtering method proposed to overcome the shortcomings of the standard mean filtering method.Shao ChongleiKaur PreetKumar RajeevDe Gruyterarticlemetallographic imageadaptive weighted mean filteringaverage filteringmedian filteringScienceQElectronic computers. Computer scienceQA75.5-76.95ENJournal of Intelligent Systems, Vol 30, Iss 1, Pp 470-478 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	metallographic image adaptive weighted mean filtering average filtering median filtering Science Q Electronic computers. Computer science QA75.5-76.95
spellingShingle	metallographic image adaptive weighted mean filtering average filtering median filtering Science Q Electronic computers. Computer science QA75.5-76.95 Shao Chonglei Kaur Preet Kumar Rajeev An Improved Adaptive Weighted Mean Filtering Approach for Metallographic Image Processing
description	As noise brings great error in the analysis of metallographic images, an adaptive weighted mean filtering method proposed to overcome the shortcomings of the standard mean filtering method.
format	article
author	Shao Chonglei Kaur Preet Kumar Rajeev
author_facet	Shao Chonglei Kaur Preet Kumar Rajeev
author_sort	Shao Chonglei
title	An Improved Adaptive Weighted Mean Filtering Approach for Metallographic Image Processing
title_short	An Improved Adaptive Weighted Mean Filtering Approach for Metallographic Image Processing
title_full	An Improved Adaptive Weighted Mean Filtering Approach for Metallographic Image Processing
title_fullStr	An Improved Adaptive Weighted Mean Filtering Approach for Metallographic Image Processing
title_full_unstemmed	An Improved Adaptive Weighted Mean Filtering Approach for Metallographic Image Processing
title_sort	improved adaptive weighted mean filtering approach for metallographic image processing
publisher	De Gruyter
publishDate	2021
url	https://doaj.org/article/721eb0b503a84d3a9cc482bded6fc035
work_keys_str_mv	AT shaochonglei animprovedadaptiveweightedmeanfilteringapproachformetallographicimageprocessing AT kaurpreet animprovedadaptiveweightedmeanfilteringapproachformetallographicimageprocessing AT kumarrajeev animprovedadaptiveweightedmeanfilteringapproachformetallographicimageprocessing AT shaochonglei improvedadaptiveweightedmeanfilteringapproachformetallographicimageprocessing AT kaurpreet improvedadaptiveweightedmeanfilteringapproachformetallographicimageprocessing AT kumarrajeev improvedadaptiveweightedmeanfilteringapproachformetallographicimageprocessing
_version_	1718371672168333312

An Improved Adaptive Weighted Mean Filtering Approach for Metallographic Image Processing

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