Computing Multivalued Mathematical Morphology on Multiband Images Using Algorithms for Multicriteria Analysis
Mathematical morphology (MM) is a powerful tool for spatial multispectral and hyperspectral image analyses. However, MM was originally developed for single-band images in which each pixel is represented by a numerical value. The most commonly used method for extending MM to multiband images is to p...
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| Format: | Article |
| Language: | English |
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Slovenian Society for Stereology and Quantitative Image Analysis
2024-03-01
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| Series: | Image Analysis and Stereology |
| Subjects: | |
| Online Access: | https://www.ias-iss.org/ojs/IAS/article/view/3042 |
| _version_ | 1797216381337337856 |
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| author | Samir L'haddad Akila Kemmouche Aude Nuscia Taïbi |
| author_facet | Samir L'haddad Akila Kemmouche Aude Nuscia Taïbi |
| author_sort | Samir L'haddad |
| collection | DOAJ |
| description |
Mathematical morphology (MM) is a powerful tool for spatial multispectral and hyperspectral image analyses. However, MM was originally developed for single-band images in which each pixel is represented by a numerical value. The most commonly used method for extending MM to multiband images is to process each band independently without considering its correlations with other bands. This can lead to the creation of artificial false spectral signatures and result in object misidentification. Therefore, extending MM to multiband images requires the use of an adequate vector ordering strategy to fully exploit its potential. This work proposes new vector ordering algorithms for the computation of multivalued MM. A multicriteria analysis (MCA) system is used as a tool for establishing an ordering of vectors. Two MCA approaches, namely, an "analytic hierarchy process" and a "preference ranking organization method for enrichment evaluation," are developed to define ordering relations between vectors. To ensure the validity of the proposed vector ordering algorithms, the computed multivalued morphological profiles are compared using the proposed vector ordering approaches and conventional schemes. The results of applying the proposed vector ordering algorithms for computing morphological profiles show that good classification accuracies were achieved for urban structures in ROSIS hyperspectral images.
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| first_indexed | 2024-04-24T11:45:03Z |
| format | Article |
| id | doaj.art-a1839bb22aa745f0aac2a4270110f25b |
| institution | Directory Open Access Journal |
| issn | 1580-3139 1854-5165 |
| language | English |
| last_indexed | 2024-04-24T11:45:03Z |
| publishDate | 2024-03-01 |
| publisher | Slovenian Society for Stereology and Quantitative Image Analysis |
| record_format | Article |
| series | Image Analysis and Stereology |
| spelling | doaj.art-a1839bb22aa745f0aac2a4270110f25b2024-04-09T11:16:56ZengSlovenian Society for Stereology and Quantitative Image AnalysisImage Analysis and Stereology1580-31391854-51652024-03-0143110.5566/ias.3042Computing Multivalued Mathematical Morphology on Multiband Images Using Algorithms for Multicriteria AnalysisSamir L'haddad0Akila Kemmouche1Aude Nuscia Taïbi2University of Sciences and Technology Houari Boumediene, Faculty of Electrical Engineering, Department of Telecommunication.University of Sciences and Technology Houari Boumediene, Faculty of Electrical Engineering, Department of Telecommunication, BP32 El Alia Bab Ezzouar, Algiers, Algeria, 16111University of Angers, CNRS, ESO, SFR CONFLUENCES, 5 bis Boulevard Lavoisier, F-49000 Angers, France Mathematical morphology (MM) is a powerful tool for spatial multispectral and hyperspectral image analyses. However, MM was originally developed for single-band images in which each pixel is represented by a numerical value. The most commonly used method for extending MM to multiband images is to process each band independently without considering its correlations with other bands. This can lead to the creation of artificial false spectral signatures and result in object misidentification. Therefore, extending MM to multiband images requires the use of an adequate vector ordering strategy to fully exploit its potential. This work proposes new vector ordering algorithms for the computation of multivalued MM. A multicriteria analysis (MCA) system is used as a tool for establishing an ordering of vectors. Two MCA approaches, namely, an "analytic hierarchy process" and a "preference ranking organization method for enrichment evaluation," are developed to define ordering relations between vectors. To ensure the validity of the proposed vector ordering algorithms, the computed multivalued morphological profiles are compared using the proposed vector ordering approaches and conventional schemes. The results of applying the proposed vector ordering algorithms for computing morphological profiles show that good classification accuracies were achieved for urban structures in ROSIS hyperspectral images. https://www.ias-iss.org/ojs/IAS/article/view/3042hyperspectral imagingvector orderingmultiband imagesmultivalued mathematical morphologymultivalued morphological profile |
| spellingShingle | Samir L'haddad Akila Kemmouche Aude Nuscia Taïbi Computing Multivalued Mathematical Morphology on Multiband Images Using Algorithms for Multicriteria Analysis Image Analysis and Stereology hyperspectral imaging vector ordering multiband images multivalued mathematical morphology multivalued morphological profile |
| title | Computing Multivalued Mathematical Morphology on Multiband Images Using Algorithms for Multicriteria Analysis |
| title_full | Computing Multivalued Mathematical Morphology on Multiband Images Using Algorithms for Multicriteria Analysis |
| title_fullStr | Computing Multivalued Mathematical Morphology on Multiband Images Using Algorithms for Multicriteria Analysis |
| title_full_unstemmed | Computing Multivalued Mathematical Morphology on Multiband Images Using Algorithms for Multicriteria Analysis |
| title_short | Computing Multivalued Mathematical Morphology on Multiband Images Using Algorithms for Multicriteria Analysis |
| title_sort | computing multivalued mathematical morphology on multiband images using algorithms for multicriteria analysis |
| topic | hyperspectral imaging vector ordering multiband images multivalued mathematical morphology multivalued morphological profile |
| url | https://www.ias-iss.org/ojs/IAS/article/view/3042 |
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