Criterion for designing adaptive filters based on segregation of grey levels in SAR images

In boundary zones (edges) in synthetic apertue radar (SAR) images, there is no logical (scientific) explanation for employing the kernel average for approximating the backscattering factors in central kernel pixels. Therefore, adaptive filters are used to decrease the speckles in these images. These...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Electronics letters 2015-06, Vol.51 (12), p.935-937
Hauptverfasser: Sahebi, M.R, Heidarian, A
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 937
container_issue 12
container_start_page 935
container_title Electronics letters
container_volume 51
creator Sahebi, M.R
Heidarian, A
description In boundary zones (edges) in synthetic apertue radar (SAR) images, there is no logical (scientific) explanation for employing the kernel average for approximating the backscattering factors in central kernel pixels. Therefore, adaptive filters are used to decrease the speckles in these images. These filters prevent the averaging process in the edges when smoothing the images (noise reduction) in homogeneous areas, thus causing reduction of lucidity in the edges. In most existing adaptive filters, the variation coefficient (coefficient of variation) is used to detect the edges in the images. An alternative factor is introduced to detect the edges in intensity images; by employing this factor, an adaptive filter is presented. The results of evaluating this filter and comparing it with other adaptive filters illustrate that it has excellent competency in speckle reduction, and hence it protects the edges of the images during the filtering process. using various assessment measures (such as signal-to-noise ratio and mean absolute error), the obtained results provide evidence that the proposed filtering process outperforms other classical methodologies.
doi_str_mv 10.1049/el.2014.4178
format Article
fullrecord <record><control><sourceid>proquest_24P</sourceid><recordid>TN_cdi_proquest_miscellaneous_1808084945</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1808084945</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4141-b4fb4efa67cb5f90fde0d911249169d39b6699abf201b927fac805877c3296393</originalsourceid><addsrcrecordid>eNp90E1LwzAYB_AgCo65mx8gBw8e7Eza9CXHOZwKA8EXEC8haZ-USNbWpJvs25tSQQWRHELg9w__50HolJI5JYxfgp3HhLI5o3lxgCY0SUnEKX05RBNCaBKllLNjNPPeqMAoywijE_S6dKYHZ9oG69bhCrypG9PUWFay680OsDY2AI-V9FDh4DzUDmrZD5lW4_DYYws7sB6bBj8uHrDZyBr8CTrS0nqYfd1T9Ly6flreRuv7m7vlYh2VoQWNFNOKgZZZXqpUc6IrIFUoHjNOM14lXGUZ51LpMJ3ica5lWZC0yPMyiXmW8GSKzsd_O9e-b8H3YmN8CdbKBtqtF7Qg4TDO0kAvRlq61nsHWnQulHV7QYkYtijAimGLYthi4OnIP4yF_b9WXK_X8dWKxBmjIXc25gz04q3duibMH8QP3lX6u_gv9meTT-YJjTM</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1808084945</pqid></control><display><type>article</type><title>Criterion for designing adaptive filters based on segregation of grey levels in SAR images</title><source>Wiley Online Library Open Access</source><creator>Sahebi, M.R ; Heidarian, A</creator><creatorcontrib>Sahebi, M.R ; Heidarian, A</creatorcontrib><description>In boundary zones (edges) in synthetic apertue radar (SAR) images, there is no logical (scientific) explanation for employing the kernel average for approximating the backscattering factors in central kernel pixels. Therefore, adaptive filters are used to decrease the speckles in these images. These filters prevent the averaging process in the edges when smoothing the images (noise reduction) in homogeneous areas, thus causing reduction of lucidity in the edges. In most existing adaptive filters, the variation coefficient (coefficient of variation) is used to detect the edges in the images. An alternative factor is introduced to detect the edges in intensity images; by employing this factor, an adaptive filter is presented. The results of evaluating this filter and comparing it with other adaptive filters illustrate that it has excellent competency in speckle reduction, and hence it protects the edges of the images during the filtering process. using various assessment measures (such as signal-to-noise ratio and mean absolute error), the obtained results provide evidence that the proposed filtering process outperforms other classical methodologies.</description><identifier>ISSN: 0013-5194</identifier><identifier>ISSN: 1350-911X</identifier><identifier>EISSN: 1350-911X</identifier><identifier>DOI: 10.1049/el.2014.4178</identifier><language>eng</language><publisher>The Institution of Engineering and Technology</publisher><subject>Adaptive filters ; backscattering factors ; central kernel pixels ; Coefficient of variation ; edge detection ; Filtering ; Filtration ; grey level segregation ; image denoising ; Image detection ; image noise reduction ; image smoothing ; image speckle reduction ; intensity images ; Kernels ; Radar, sonar and navigation ; Reduction ; SAR images ; speckle ; successive‐approximation resistor images ; variation coefficient</subject><ispartof>Electronics letters, 2015-06, Vol.51 (12), p.935-937</ispartof><rights>The Institution of Engineering and Technology</rights><rights>2020 The Institution of Engineering and Technology</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4141-b4fb4efa67cb5f90fde0d911249169d39b6699abf201b927fac805877c3296393</citedby><cites>FETCH-LOGICAL-c4141-b4fb4efa67cb5f90fde0d911249169d39b6699abf201b927fac805877c3296393</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1049%2Fel.2014.4178$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1049%2Fel.2014.4178$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,777,781,1412,11543,27905,27906,45555,45556,46033,46457</link.rule.ids><linktorsrc>$$Uhttps://onlinelibrary.wiley.com/doi/abs/10.1049%2Fel.2014.4178$$EView_record_in_Wiley-Blackwell$$FView_record_in_$$GWiley-Blackwell</linktorsrc></links><search><creatorcontrib>Sahebi, M.R</creatorcontrib><creatorcontrib>Heidarian, A</creatorcontrib><title>Criterion for designing adaptive filters based on segregation of grey levels in SAR images</title><title>Electronics letters</title><description>In boundary zones (edges) in synthetic apertue radar (SAR) images, there is no logical (scientific) explanation for employing the kernel average for approximating the backscattering factors in central kernel pixels. Therefore, adaptive filters are used to decrease the speckles in these images. These filters prevent the averaging process in the edges when smoothing the images (noise reduction) in homogeneous areas, thus causing reduction of lucidity in the edges. In most existing adaptive filters, the variation coefficient (coefficient of variation) is used to detect the edges in the images. An alternative factor is introduced to detect the edges in intensity images; by employing this factor, an adaptive filter is presented. The results of evaluating this filter and comparing it with other adaptive filters illustrate that it has excellent competency in speckle reduction, and hence it protects the edges of the images during the filtering process. using various assessment measures (such as signal-to-noise ratio and mean absolute error), the obtained results provide evidence that the proposed filtering process outperforms other classical methodologies.</description><subject>Adaptive filters</subject><subject>backscattering factors</subject><subject>central kernel pixels</subject><subject>Coefficient of variation</subject><subject>edge detection</subject><subject>Filtering</subject><subject>Filtration</subject><subject>grey level segregation</subject><subject>image denoising</subject><subject>Image detection</subject><subject>image noise reduction</subject><subject>image smoothing</subject><subject>image speckle reduction</subject><subject>intensity images</subject><subject>Kernels</subject><subject>Radar, sonar and navigation</subject><subject>Reduction</subject><subject>SAR images</subject><subject>speckle</subject><subject>successive‐approximation resistor images</subject><subject>variation coefficient</subject><issn>0013-5194</issn><issn>1350-911X</issn><issn>1350-911X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNp90E1LwzAYB_AgCo65mx8gBw8e7Eza9CXHOZwKA8EXEC8haZ-USNbWpJvs25tSQQWRHELg9w__50HolJI5JYxfgp3HhLI5o3lxgCY0SUnEKX05RBNCaBKllLNjNPPeqMAoywijE_S6dKYHZ9oG69bhCrypG9PUWFay680OsDY2AI-V9FDh4DzUDmrZD5lW4_DYYws7sB6bBj8uHrDZyBr8CTrS0nqYfd1T9Ly6flreRuv7m7vlYh2VoQWNFNOKgZZZXqpUc6IrIFUoHjNOM14lXGUZ51LpMJ3ica5lWZC0yPMyiXmW8GSKzsd_O9e-b8H3YmN8CdbKBtqtF7Qg4TDO0kAvRlq61nsHWnQulHV7QYkYtijAimGLYthi4OnIP4yF_b9WXK_X8dWKxBmjIXc25gz04q3duibMH8QP3lX6u_gv9meTT-YJjTM</recordid><startdate>20150611</startdate><enddate>20150611</enddate><creator>Sahebi, M.R</creator><creator>Heidarian, A</creator><general>The Institution of Engineering and Technology</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>L7M</scope></search><sort><creationdate>20150611</creationdate><title>Criterion for designing adaptive filters based on segregation of grey levels in SAR images</title><author>Sahebi, M.R ; Heidarian, A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4141-b4fb4efa67cb5f90fde0d911249169d39b6699abf201b927fac805877c3296393</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Adaptive filters</topic><topic>backscattering factors</topic><topic>central kernel pixels</topic><topic>Coefficient of variation</topic><topic>edge detection</topic><topic>Filtering</topic><topic>Filtration</topic><topic>grey level segregation</topic><topic>image denoising</topic><topic>Image detection</topic><topic>image noise reduction</topic><topic>image smoothing</topic><topic>image speckle reduction</topic><topic>intensity images</topic><topic>Kernels</topic><topic>Radar, sonar and navigation</topic><topic>Reduction</topic><topic>SAR images</topic><topic>speckle</topic><topic>successive‐approximation resistor images</topic><topic>variation coefficient</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sahebi, M.R</creatorcontrib><creatorcontrib>Heidarian, A</creatorcontrib><collection>CrossRef</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Engineering Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Electronics letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Sahebi, M.R</au><au>Heidarian, A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Criterion for designing adaptive filters based on segregation of grey levels in SAR images</atitle><jtitle>Electronics letters</jtitle><date>2015-06-11</date><risdate>2015</risdate><volume>51</volume><issue>12</issue><spage>935</spage><epage>937</epage><pages>935-937</pages><issn>0013-5194</issn><issn>1350-911X</issn><eissn>1350-911X</eissn><abstract>In boundary zones (edges) in synthetic apertue radar (SAR) images, there is no logical (scientific) explanation for employing the kernel average for approximating the backscattering factors in central kernel pixels. Therefore, adaptive filters are used to decrease the speckles in these images. These filters prevent the averaging process in the edges when smoothing the images (noise reduction) in homogeneous areas, thus causing reduction of lucidity in the edges. In most existing adaptive filters, the variation coefficient (coefficient of variation) is used to detect the edges in the images. An alternative factor is introduced to detect the edges in intensity images; by employing this factor, an adaptive filter is presented. The results of evaluating this filter and comparing it with other adaptive filters illustrate that it has excellent competency in speckle reduction, and hence it protects the edges of the images during the filtering process. using various assessment measures (such as signal-to-noise ratio and mean absolute error), the obtained results provide evidence that the proposed filtering process outperforms other classical methodologies.</abstract><pub>The Institution of Engineering and Technology</pub><doi>10.1049/el.2014.4178</doi><tpages>3</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 0013-5194
ispartof Electronics letters, 2015-06, Vol.51 (12), p.935-937
issn 0013-5194
1350-911X
1350-911X
language eng
recordid cdi_proquest_miscellaneous_1808084945
source Wiley Online Library Open Access
subjects Adaptive filters
backscattering factors
central kernel pixels
Coefficient of variation
edge detection
Filtering
Filtration
grey level segregation
image denoising
Image detection
image noise reduction
image smoothing
image speckle reduction
intensity images
Kernels
Radar, sonar and navigation
Reduction
SAR images
speckle
successive‐approximation resistor images
variation coefficient
title Criterion for designing adaptive filters based on segregation of grey levels in SAR images
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-20T08%3A30%3A08IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_24P&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Criterion%20for%20designing%20adaptive%20filters%20based%20on%20segregation%20of%20grey%20levels%20in%20SAR%20images&rft.jtitle=Electronics%20letters&rft.au=Sahebi,%20M.R&rft.date=2015-06-11&rft.volume=51&rft.issue=12&rft.spage=935&rft.epage=937&rft.pages=935-937&rft.issn=0013-5194&rft.eissn=1350-911X&rft_id=info:doi/10.1049/el.2014.4178&rft_dat=%3Cproquest_24P%3E1808084945%3C/proquest_24P%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1808084945&rft_id=info:pmid/&rfr_iscdi=true