{"title":"基于聚类和单层神经网络的无监督高光谱波段选择","authors":"Mateus Habermann, V. Fremont, E. H. Shiguemori","doi":"10.52638/rfpt.2018.419","DOIUrl":null,"url":null,"abstract":"Hyperspectral images provide rich spectral details of the observed scene by exploiting contiguous bands.But, the processing of such images becomes heavy, due to the high dimensionality.Thus, band selection is a practice that has been adopted before any further processing takes place.Therefore, in this paper, a new unsupervised method for band selection based on clustering and neural network is proposed. A comparison with six other band selection frameworks shows the strength of the proposed method.","PeriodicalId":285609,"journal":{"name":"Revue Française de Photogrammétrie et de Télédétection","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Unsupervised Hyperspectral Band Selection using Clustering and Single-Layer Neural Network\",\"authors\":\"Mateus Habermann, V. Fremont, E. H. Shiguemori\",\"doi\":\"10.52638/rfpt.2018.419\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hyperspectral images provide rich spectral details of the observed scene by exploiting contiguous bands.But, the processing of such images becomes heavy, due to the high dimensionality.Thus, band selection is a practice that has been adopted before any further processing takes place.Therefore, in this paper, a new unsupervised method for band selection based on clustering and neural network is proposed. A comparison with six other band selection frameworks shows the strength of the proposed method.\",\"PeriodicalId\":285609,\"journal\":{\"name\":\"Revue Française de Photogrammétrie et de Télédétection\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Revue Française de Photogrammétrie et de Télédétection\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52638/rfpt.2018.419\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revue Française de Photogrammétrie et de Télédétection","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52638/rfpt.2018.419","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Unsupervised Hyperspectral Band Selection using Clustering and Single-Layer Neural Network
Hyperspectral images provide rich spectral details of the observed scene by exploiting contiguous bands.But, the processing of such images becomes heavy, due to the high dimensionality.Thus, band selection is a practice that has been adopted before any further processing takes place.Therefore, in this paper, a new unsupervised method for band selection based on clustering and neural network is proposed. A comparison with six other band selection frameworks shows the strength of the proposed method.