R. P. Iyer, Archanaa Raveendran, S. Bhuvana, R. Kavitha
{"title":"遥感高光谱图像分析技术","authors":"R. P. Iyer, Archanaa Raveendran, S. Bhuvana, R. Kavitha","doi":"10.1109/SSPS.2017.8071626","DOIUrl":null,"url":null,"abstract":"This article presents an overview of hyperspectral image analysis and processing techniques based on remote sensing. Image analysis methods will be explained in detail. A general framework is presented for working with hyperspectral imagery, including removal of atmospheric effects. Due to large dimensionality of the feature space, hyperspectral data poses a challenge to image interpretation in the following ways: 1) need of calibration of data2) redundancy in information and 3) high volume data. Hence, a brief discussion on dimensionality reduction will also be presented in this review.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Hyperspectral image analysis techniques on remote sensing\",\"authors\":\"R. P. Iyer, Archanaa Raveendran, S. Bhuvana, R. Kavitha\",\"doi\":\"10.1109/SSPS.2017.8071626\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents an overview of hyperspectral image analysis and processing techniques based on remote sensing. Image analysis methods will be explained in detail. A general framework is presented for working with hyperspectral imagery, including removal of atmospheric effects. Due to large dimensionality of the feature space, hyperspectral data poses a challenge to image interpretation in the following ways: 1) need of calibration of data2) redundancy in information and 3) high volume data. Hence, a brief discussion on dimensionality reduction will also be presented in this review.\",\"PeriodicalId\":382353,\"journal\":{\"name\":\"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSPS.2017.8071626\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSPS.2017.8071626","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hyperspectral image analysis techniques on remote sensing
This article presents an overview of hyperspectral image analysis and processing techniques based on remote sensing. Image analysis methods will be explained in detail. A general framework is presented for working with hyperspectral imagery, including removal of atmospheric effects. Due to large dimensionality of the feature space, hyperspectral data poses a challenge to image interpretation in the following ways: 1) need of calibration of data2) redundancy in information and 3) high volume data. Hence, a brief discussion on dimensionality reduction will also be presented in this review.