{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T22:19:59Z","timestamp":1784585999127,"version":"3.55.0"},"reference-count":30,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2016,1,26]],"date-time":"2016-01-26T00:00:00Z","timestamp":1453766400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"International Science and Technology Collaboration Project of China","award":["2010DFA92720-24"],"award-info":[{"award-number":["2010DFA92720-24"]}]},{"name":"National Natural Science Foundation program","award":["41301403"],"award-info":[{"award-number":["41301403"]}]},{"name":"National Natural Science Foundation program","award":["41471340"],"award-info":[{"award-number":["41471340"]}]},{"name":"Research Grants Council (RGC) of Hong Kong General Research Fund","award":["203913"],"award-info":[{"award-number":["203913"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Hyperspectral images possess properties such as rich spectral information, narrow bandwidth, and large numbers of bands. Finding effective methods to retrieve land features from an image by using similarity assessment indices with specific spectral characteristics is an important research question. This paper reports a novel hyperspectral image similarity assessment index based on spectral curve patterns and a reflection-absorption index. First, some spectral reflection-absorption features are extracted to restrict the subsequent curve simplification. Then, the improved Douglas-Peucker algorithm is employed to simplify all spectral curves without setting the thresholds. Finally, the simplified curves with the feature points are matched, and the similarities among the spectral curves are calculated using the matched points. The Airborne Visible Infrared Imaging Spectrometer (AVIRIS) and Reflective Optics System Imaging Spectrometer (ROSIS) hyperspectral image datasets are then selected to test the effect of the proposed index. The practical experiments indicate that the proposed index can achieve higher precision and fewer points than the traditional spectral information divergence and spectral angle match.<\/jats:p>","DOI":"10.3390\/s16020152","type":"journal-article","created":{"date-parts":[[2016,1,26]],"date-time":"2016-01-26T10:00:42Z","timestamp":1453802442000},"page":"152","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Spectral Similarity Assessment Based on a Spectrum Reflectance-Absorption Index and Simplified Curve Patterns for Hyperspectral Remote Sensing"],"prefix":"10.3390","volume":"16","author":[{"given":"Dan","family":"Ma","sequence":"first","affiliation":[{"name":"College of Resource and Environmental Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7280-1443","authenticated-orcid":false,"given":"Jun","family":"Liu","sequence":"additional","affiliation":[{"name":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0605-6713","authenticated-orcid":false,"given":"Junyi","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Geography, Hong Kong Baptist University, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huali","family":"Li","sequence":"additional","affiliation":[{"name":"College of Electrical and Information Engineering, Hunan University, Hunan 410082, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ping","family":"Liu","sequence":"additional","affiliation":[{"name":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huijuan","family":"Chen","sequence":"additional","affiliation":[{"name":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Qian","sequence":"additional","affiliation":[{"name":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2016,1,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"25663","DOI":"10.3390\/s151025663","article-title":"True Colour Classification of Natural Waters with Medium-Spectral Resolution Satellites: SeaWiFS, MODIS, MERIS and OLCI","volume":"15","author":"Wernand","year":"2015","journal-title":"Sensors"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"15578","DOI":"10.3390\/s150715578","article-title":"Spectral and Image Integrated Analysis of Hyperspectral Data for Waxy Corn Seed Variety Classification","volume":"15","author":"Yang","year":"2015","journal-title":"Sensors"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"17234","DOI":"10.3390\/s121217234","article-title":"Application of Hyperspectral Imaging and Chemometric Calibrations for Variety Discrimination of Maize Seeds","volume":"12","author":"Zhang","year":"2012","journal-title":"Sensors"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"22956","DOI":"10.3390\/s150922956","article-title":"Evaluating Sentinel-2 for Lakeshore Habitat Mapping Based on Airborne Hyperspectral Data","volume":"15","author":"Stratoulias","year":"2015","journal-title":"Sensors"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"10639","DOI":"10.3390\/s120810639","article-title":"Hyperspectral Analysis of Soil Nitrogen, Carbon, Carbonate, and Organic Matter Using Regression Trees","volume":"12","author":"Gmur","year":"2012","journal-title":"Sensors"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1588","DOI":"10.1109\/36.841986","article-title":"Compression of multispectral remote sensing images using clustering and spectral reduction","volume":"38","author":"Kaarna","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1177\/1094342007088380","article-title":"Low-complexity principal component analysis for hyperspectral image compression","volume":"22","author":"Du","year":"2008","journal-title":"Int. J. High Perform. Comput. Appl."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1586","DOI":"10.1109\/TGRS.2005.863297","article-title":"Independent component analysis-based dimensionality reduction with applications in hyperspectral image analysis","volume":"44","author":"Wang","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"522","DOI":"10.1109\/LGRS.2006.878240","article-title":"Band selection for hyperspectral image classification using mutual information","volume":"3","author":"Guo","year":"2006","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2653","DOI":"10.1109\/36.803413","article-title":"Hyperspectral data analysis and supervised feature reduction via projection pursuit","volume":"37","author":"Jimenez","year":"1999","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3551","DOI":"10.1080\/01431161003698302","article-title":"Improving within-genus tree species discrimination using the discrete wavelet transform applied to airborne hyperspectral data","volume":"32","author":"Banskota","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1109\/TGRS.2008.2002953","article-title":"Experimental approach to the selection of the components in the minimum noise fraction","volume":"47","author":"Amato","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","unstructured":"Licciardi, G.A., and Frate, F.D. (2010, January 17\u201319). A comparison of feature extraction methodologies applied on hyperspectral data. Proceedings of ESA Hyperspectral 2010 Workshop, Frascati, Italy."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"538","DOI":"10.1109\/36.739109","article-title":"Segmented prineipal components transformation for efficient hyperspectral remote sensing image display and classification","volume":"37","author":"Jia","year":"1999","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"4311","DOI":"10.1080\/01431161.2010.486416","article-title":"Using class-based feature selection for the classification of hyperspectral data","volume":"32","author":"Maghsoudi","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/S0168-1699(03)00020-6","article-title":"Classification of hyperspectral data by decision trees and artificial neural networks to identify weed stress and nitrogen status of corn","volume":"39","author":"Goel","year":"2003","journal-title":"Comput. Electron. Agric."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"736","DOI":"10.1109\/LGRS.2010.2047711","article-title":"SVM- and MRF-based method for accurate classification of hyperspectral images","volume":"7","author":"Tarabalka","year":"2010","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/0034-4257(93)90013-N","article-title":"The spectral image processing system (SIPS)\u2013interactive visualization and analysis of imaging spectrometer data","volume":"44","author":"Kruse","year":"1993","journal-title":"Remote Sens. Environ."},{"key":"ref_19","first-page":"100","article-title":"Extraction of first derivative spectrum features ofsoil organic matter via wavelet de-noising","volume":"31","author":"Liu","year":"2011","journal-title":"Spectrosc. Spectr. Anal."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"986","DOI":"10.1109\/TMI.2003.815867","article-title":"Mutual information based registration of medical images: A survey","volume":"22","author":"Pluim","year":"2003","journal-title":"IEEE Trans. Med. Imag."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1927","DOI":"10.1109\/18.857802","article-title":"An information-theoretic approach to spectral variability, similarity, and discrimination for hyperspectral image analysis","volume":"46","author":"Chang","year":"2000","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_22","first-page":"77","article-title":"Automated tongue segmentation algorithm based on hyperspectral image","volume":"26","author":"Li","year":"2007","journal-title":"J. Infrared Millim. Waves"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1777","DOI":"10.1117\/1.1766301","article-title":"New hyperspectral discrimination measure for spectral characterization","volume":"43","author":"Du","year":"2004","journal-title":"Opt. Eng."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"4041","DOI":"10.1080\/01431161.2010.484431","article-title":"A new hybrid spectral similarity measure for discrimination among Vigna species","volume":"32","author":"Kumar","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","first-page":"2166","article-title":"A new spectral similarity measure based on multiple features integration","volume":"31","author":"Kong","year":"2011","journal-title":"Spectrosc. Spectr. Anal."},{"key":"ref_26","first-page":"1171","article-title":"Spectral feature-based hyperspectral RS image retrieval","volume":"25","author":"Du","year":"2005","journal-title":"Spectrosc. Spectr. Anal."},{"key":"ref_27","first-page":"715","article-title":"Spectral characteristics of corn under different nitrogen treatments","volume":"30","author":"Sun","year":"2010","journal-title":"Spectrosc. Spectr. Anal."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/j.rse.2005.03.009","article-title":"Hyperspectral discrimination of tropical rain forest tree species at leaf to crown scales","volume":"96","author":"Clark","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/S0924-2716(02)00060-6","article-title":"Hyperspectral edge filtering for measuring homo-geneity of surface cover types","volume":"56","author":"Bakker","year":"2002","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_30","unstructured":"Du, Y., Ives, R., Etter, D., Welch, T., and Chang, C.-I. (2004, January 12\u201316). A one-dimensional approach for iris recognition. Proceedings of the SPIE Biometric Technology for Human Identification, Orlando, FL, USA."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/16\/2\/152\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:18:18Z","timestamp":1760210298000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/16\/2\/152"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,1,26]]},"references-count":30,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2016,2]]}},"alternative-id":["s16020152"],"URL":"https:\/\/doi.org\/10.3390\/s16020152","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,1,26]]}}}