Loading…
Nonlocal and multivariate mathematical morphology
The generalization of mathematical morphology to multivariate images is addressed in this paper. The proposed approach is fully unsupervised and consists in constructing a complete lattice from an image as a rank transformation together with a learned ordering of vectors. This unsupervised ordering...
Saved in:
Main Authors: | , |
---|---|
Format: | Conference Proceeding |
Language: | English |
Subjects: | |
Online Access: | Request full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | |
---|---|
cites | |
container_end_page | 132 |
container_issue | |
container_start_page | 129 |
container_title | |
container_volume | |
creator | Lezoray, O. Elmoataz, A. |
description | The generalization of mathematical morphology to multivariate images is addressed in this paper. The proposed approach is fully unsupervised and consists in constructing a complete lattice from an image as a rank transformation together with a learned ordering of vectors. This unsupervised ordering of vectors relies on three steps: dictionary learning, manifold learning and out of sample extension. In addition to providing an efficient way to construct a vectorial ordering, nonlocal configurations based on color patches can be easily handled and provide much better results than with classical local morphological approaches. |
doi_str_mv | 10.1109/ICIP.2012.6466812 |
format | conference_proceeding |
fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_6466812</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6466812</ieee_id><sourcerecordid>6466812</sourcerecordid><originalsourceid>FETCH-LOGICAL-h252t-798baade8692720e7776de478af25d53510ab2dd01440b17119b0bcc5d2986453</originalsourceid><addsrcrecordid>eNo1j8tKw1AURY8vMK39AHHSH0g859z3UIKPQFEHOi43ubcmkjQliUL_3op1stdgwYINcE2YEaG7LfLiNWMkzrTU2hKfwMIZS1IbwUoIPoWEhaXUKunOYPYvJJ1DQoo5ldbiJczG8RPxEBKUAD3327avfLv027Dsvtqp-fZD46e47PxUx8M0v7brh13dt_3H_gouNr4d4-LIObw_3L_lT-nq5bHI71ZpzYqn1Dhbeh-i1Y4NYzTG6BClsX7DKiihCH3JISBJiSUZIldiWVUqsLNaKjGHm79uE2Nc74am88N-fbwufgBkDEfl</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Nonlocal and multivariate mathematical morphology</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Lezoray, O. ; Elmoataz, A.</creator><creatorcontrib>Lezoray, O. ; Elmoataz, A.</creatorcontrib><description>The generalization of mathematical morphology to multivariate images is addressed in this paper. The proposed approach is fully unsupervised and consists in constructing a complete lattice from an image as a rank transformation together with a learned ordering of vectors. This unsupervised ordering of vectors relies on three steps: dictionary learning, manifold learning and out of sample extension. In addition to providing an efficient way to construct a vectorial ordering, nonlocal configurations based on color patches can be easily handled and provide much better results than with classical local morphological approaches.</description><identifier>ISSN: 1522-4880</identifier><identifier>ISBN: 1467325341</identifier><identifier>ISBN: 9781467325349</identifier><identifier>EISSN: 2381-8549</identifier><identifier>EISBN: 9781467325332</identifier><identifier>EISBN: 1467325325</identifier><identifier>EISBN: 9781467325325</identifier><identifier>EISBN: 1467325333</identifier><identifier>DOI: 10.1109/ICIP.2012.6466812</identifier><language>eng</language><publisher>IEEE</publisher><subject>Dictionaries ; Image color analysis ; Laplace equations ; Lattices ; manifold learning ; Manifolds ; Mathematical morphology ; Morphology ; multivariate ; nonlocal ; Vectors</subject><ispartof>2012 19th IEEE International Conference on Image Processing, 2012, p.129-132</ispartof><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6466812$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54555,54920,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6466812$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Lezoray, O.</creatorcontrib><creatorcontrib>Elmoataz, A.</creatorcontrib><title>Nonlocal and multivariate mathematical morphology</title><title>2012 19th IEEE International Conference on Image Processing</title><addtitle>ICIP</addtitle><description>The generalization of mathematical morphology to multivariate images is addressed in this paper. The proposed approach is fully unsupervised and consists in constructing a complete lattice from an image as a rank transformation together with a learned ordering of vectors. This unsupervised ordering of vectors relies on three steps: dictionary learning, manifold learning and out of sample extension. In addition to providing an efficient way to construct a vectorial ordering, nonlocal configurations based on color patches can be easily handled and provide much better results than with classical local morphological approaches.</description><subject>Dictionaries</subject><subject>Image color analysis</subject><subject>Laplace equations</subject><subject>Lattices</subject><subject>manifold learning</subject><subject>Manifolds</subject><subject>Mathematical morphology</subject><subject>Morphology</subject><subject>multivariate</subject><subject>nonlocal</subject><subject>Vectors</subject><issn>1522-4880</issn><issn>2381-8549</issn><isbn>1467325341</isbn><isbn>9781467325349</isbn><isbn>9781467325332</isbn><isbn>1467325325</isbn><isbn>9781467325325</isbn><isbn>1467325333</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1j8tKw1AURY8vMK39AHHSH0g859z3UIKPQFEHOi43ubcmkjQliUL_3op1stdgwYINcE2YEaG7LfLiNWMkzrTU2hKfwMIZS1IbwUoIPoWEhaXUKunOYPYvJJ1DQoo5ldbiJczG8RPxEBKUAD3327avfLv027Dsvtqp-fZD46e47PxUx8M0v7brh13dt_3H_gouNr4d4-LIObw_3L_lT-nq5bHI71ZpzYqn1Dhbeh-i1Y4NYzTG6BClsX7DKiihCH3JISBJiSUZIldiWVUqsLNaKjGHm79uE2Nc74am88N-fbwufgBkDEfl</recordid><startdate>201209</startdate><enddate>201209</enddate><creator>Lezoray, O.</creator><creator>Elmoataz, A.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201209</creationdate><title>Nonlocal and multivariate mathematical morphology</title><author>Lezoray, O. ; Elmoataz, A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-h252t-798baade8692720e7776de478af25d53510ab2dd01440b17119b0bcc5d2986453</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Dictionaries</topic><topic>Image color analysis</topic><topic>Laplace equations</topic><topic>Lattices</topic><topic>manifold learning</topic><topic>Manifolds</topic><topic>Mathematical morphology</topic><topic>Morphology</topic><topic>multivariate</topic><topic>nonlocal</topic><topic>Vectors</topic><toplevel>online_resources</toplevel><creatorcontrib>Lezoray, O.</creatorcontrib><creatorcontrib>Elmoataz, A.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library Online</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Lezoray, O.</au><au>Elmoataz, A.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Nonlocal and multivariate mathematical morphology</atitle><btitle>2012 19th IEEE International Conference on Image Processing</btitle><stitle>ICIP</stitle><date>2012-09</date><risdate>2012</risdate><spage>129</spage><epage>132</epage><pages>129-132</pages><issn>1522-4880</issn><eissn>2381-8549</eissn><isbn>1467325341</isbn><isbn>9781467325349</isbn><eisbn>9781467325332</eisbn><eisbn>1467325325</eisbn><eisbn>9781467325325</eisbn><eisbn>1467325333</eisbn><abstract>The generalization of mathematical morphology to multivariate images is addressed in this paper. The proposed approach is fully unsupervised and consists in constructing a complete lattice from an image as a rank transformation together with a learned ordering of vectors. This unsupervised ordering of vectors relies on three steps: dictionary learning, manifold learning and out of sample extension. In addition to providing an efficient way to construct a vectorial ordering, nonlocal configurations based on color patches can be easily handled and provide much better results than with classical local morphological approaches.</abstract><pub>IEEE</pub><doi>10.1109/ICIP.2012.6466812</doi><tpages>4</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISSN: 1522-4880 |
ispartof | 2012 19th IEEE International Conference on Image Processing, 2012, p.129-132 |
issn | 1522-4880 2381-8549 |
language | eng |
recordid | cdi_ieee_primary_6466812 |
source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Dictionaries Image color analysis Laplace equations Lattices manifold learning Manifolds Mathematical morphology Morphology multivariate nonlocal Vectors |
title | Nonlocal and multivariate mathematical morphology |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-21T12%3A42%3A48IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Nonlocal%20and%20multivariate%20mathematical%20morphology&rft.btitle=2012%2019th%20IEEE%20International%20Conference%20on%20Image%20Processing&rft.au=Lezoray,%20O.&rft.date=2012-09&rft.spage=129&rft.epage=132&rft.pages=129-132&rft.issn=1522-4880&rft.eissn=2381-8549&rft.isbn=1467325341&rft.isbn_list=9781467325349&rft_id=info:doi/10.1109/ICIP.2012.6466812&rft.eisbn=9781467325332&rft.eisbn_list=1467325325&rft.eisbn_list=9781467325325&rft.eisbn_list=1467325333&rft_dat=%3Cieee_6IE%3E6466812%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-h252t-798baade8692720e7776de478af25d53510ab2dd01440b17119b0bcc5d2986453%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=6466812&rfr_iscdi=true |