Reduction dimensionality of hyperspectral imagery using genetic algorithm and mutual information and normalized mutual information as a fitness function

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dc.contributor.authorMaria, Merzouqi
dc.contributor.authorEl Kebir, Sarhrouni
dc.contributor.authorAhmed, Hammouch
dc.contributor.statusnemhu_HU
dc.date.accessioned2021-04-01T07:01:01Z
dc.date.available2021-04-01T07:01:01Z
dc.date.issued2021-03-20
dc.description.abstractHyperspectral images (HSI) present a wealth of information. It is distinguished by its high dimensionality. It served humanity in many fields. The quantity of HSI information represents a double-edged sword. As a consequence, their dimensionality must be reduced. Nowadays, several methods are proposed to overcome their duress. The most useful and essential solution is selection approaches of hyperspectral bands to analyze it quickly. Our work suggests a novel method to achieve this selection: we introduce a Genetic Algorithm (GA) based on mutual information (MI) and Normalized Mutual Information (NMI) as fitness functions. It selects the relevant bands from noisiest and redundant ones that don’t contain any additional information. .The proposed method is applied to three different HSI: INDIAN PINE, PAVIA, and SALINAS. The introduced algorithm provides a remarkable efficiency on the accuracy of the classification, in front of other statistical methods: the Bhattacharyya coefficient as well as the inter-bands correlation (Pearson correlation). We conclude that the measure of information (MI, NMI) provides more efficiency as a fitness function for GA selection applied to HSI; it must be more investigated.hu_HU
dc.identifier.doi10.1556/1848.2020.00149hu_HU
dc.identifier.issn2062-0810
dc.identifier.issue1hu_HU
dc.identifier.jtitleInternational Review of Applied Sciences and Engineering
dc.identifier.urihttp://hdl.handle.net/2437/305054
dc.identifier.urlhttps://akjournals.com/view/journals/1848/12/1/article-p64.xmlhu_HU
dc.identifier.volume12hu_HU
dc.language.isoenhu_HU
dc.publisherAkadémiai Kiadóhu_HU
dc.subjectreduction of dimensionalityhu_HU
dc.subjectmutual informationhu_HU
dc.subjectnormalized mutual informationhu_HU
dc.subjectgenetic algorithmhu_HU
dc.subjectSVMhu_HU
dc.titleReduction dimensionality of hyperspectral imagery using genetic algorithm and mutual information and normalized mutual information as a fitness functionhu_HU
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International Review of Applied Sciences and Engineering