{"id":"https://openalex.org/W2765156120","doi":"https://doi.org/10.1109/whispers.2015.8075491","title":"Chromatic discrimination of impervious surfaces using artificial colors for hyper spectral data","display_name":"Chromatic discrimination of impervious surfaces using artificial colors for hyper spectral data","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W2765156120","doi":"https://doi.org/10.1109/whispers.2015.8075491","mag":"2765156120"},"language":"en","primary_location":{"id":"doi:10.1109/whispers.2015.8075491","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2015.8075491","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017049098","display_name":"Shailesh Deshpande","orcid":"https://orcid.org/0000-0001-8758-2557"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shailesh Deshpande","raw_affiliation_strings":["54-B Hadapsar Industrial Estate, Tata Research Development and Design Centre, Pune, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"54-B Hadapsar Industrial Estate, Tata Research Development and Design Centre, Pune, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071800082","display_name":"Arun B. Inamdar","orcid":"https://orcid.org/0000-0002-3075-0596"},"institutions":[{"id":"https://openalex.org/I162827531","display_name":"Indian Institute of Technology Bombay","ror":"https://ror.org/02qyf5152","country_code":"IN","type":"education","lineage":["https://openalex.org/I162827531"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arun Inamdar","raw_affiliation_strings":["Centre of Studies in Resources Engineering, Indian Institute of Technology, Mumbai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centre of Studies in Resources Engineering, Indian Institute of Technology, Mumbai, India","institution_ids":["https://openalex.org/I162827531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025006858","display_name":"Harrick M. Vin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Harrick Vin","raw_affiliation_strings":["54-B Hadapsar Industrial Estate, Tata Research Development and Design Centre, Pune, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"54-B Hadapsar Industrial Estate, Tata Research Development and Design Centre, Pune, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5379,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.67592261,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"40","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9835000038146973,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11963","display_name":"Impact of Light on Environment and Health","score":0.9556999802589417,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/impervious-surface","display_name":"Impervious surface","score":0.7866137027740479},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7009823322296143},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6275268793106079},{"id":"https://openalex.org/keywords/color-model","display_name":"Color model","score":0.5864849090576172},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5547428131103516},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4948996901512146},{"id":"https://openalex.org/keywords/color-space","display_name":"Color space","score":0.45843276381492615},{"id":"https://openalex.org/keywords/color-gel","display_name":"Color gel","score":0.4362831115722656},{"id":"https://openalex.org/keywords/chromatic-scale","display_name":"Chromatic scale","score":0.4315488636493683},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4278143048286438},{"id":"https://openalex.org/keywords/color-analysis","display_name":"Color analysis","score":0.41824251413345337},{"id":"https://openalex.org/keywords/color-difference","display_name":"Color difference","score":0.4154853820800781},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.41037458181381226},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4095694422721863},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.3458199203014374},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.22130563855171204},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.18551594018936157},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.18450719118118286},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.13450437784194946},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12567752599716187},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.09372371435165405}],"concepts":[{"id":"https://openalex.org/C2668921","wikidata":"https://www.wikidata.org/wiki/Q1434713","display_name":"Impervious surface","level":2,"score":0.7866137027740479},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7009823322296143},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6275268793106079},{"id":"https://openalex.org/C36262787","wikidata":"https://www.wikidata.org/wiki/Q2294018","display_name":"Color model","level":4,"score":0.5864849090576172},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5547428131103516},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4948996901512146},{"id":"https://openalex.org/C2961294","wikidata":"https://www.wikidata.org/wiki/Q166863","display_name":"Color space","level":3,"score":0.45843276381492615},{"id":"https://openalex.org/C142771000","wikidata":"https://www.wikidata.org/wiki/Q1435398","display_name":"Color gel","level":4,"score":0.4362831115722656},{"id":"https://openalex.org/C196956537","wikidata":"https://www.wikidata.org/wiki/Q202021","display_name":"Chromatic scale","level":2,"score":0.4315488636493683},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4278143048286438},{"id":"https://openalex.org/C2777385505","wikidata":"https://www.wikidata.org/wiki/Q1396469","display_name":"Color analysis","level":2,"score":0.41824251413345337},{"id":"https://openalex.org/C186991048","wikidata":"https://www.wikidata.org/wiki/Q1184883","display_name":"Color difference","level":3,"score":0.4154853820800781},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.41037458181381226},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4095694422721863},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.3458199203014374},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.22130563855171204},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.18551594018936157},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.18450719118118286},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.13450437784194946},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12567752599716187},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.09372371435165405},{"id":"https://openalex.org/C87359718","wikidata":"https://www.wikidata.org/wiki/Q1271916","display_name":"Thin-film transistor","level":3,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/whispers.2015.8075491","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2015.8075491","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6700000166893005}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1984952790","https://openalex.org/W2043817535","https://openalex.org/W2048397240","https://openalex.org/W2146541091","https://openalex.org/W2159411209","https://openalex.org/W2170513409","https://openalex.org/W4254610561","https://openalex.org/W6776471817"],"related_works":["https://openalex.org/W146255509","https://openalex.org/W2070857196","https://openalex.org/W1969136164","https://openalex.org/W2352335641","https://openalex.org/W2364977758","https://openalex.org/W2154790816","https://openalex.org/W2164405853","https://openalex.org/W2037824874","https://openalex.org/W2084863008","https://openalex.org/W1973019807"],"abstract_inverted_index":{"Extending":[0],"color":[1,17,38,59,86,114,121,131,142],"vision":[2],"principles":[3],"to":[4,117,122,143],"display":[5],"hyperspectral":[6],"data":[7],"has":[8],"been":[9],"investigated":[10],"by":[11,19,79,97,110],"researchers":[12],"in":[13,44],"recent":[14],"past.":[15],"However,":[16],"obtained":[18],"this":[20,45],"approach":[21],"(artificial":[22],"color)":[23],"is":[24],"not":[25],"used":[26,42],"comprehensively":[27],"for":[28],"discriminating":[29],"different":[30],"materials.":[31,91],"Especially,":[32],"some":[33],"of":[34,52,60,67,87,89,133,140,147],"the":[35,129],"interesting":[36],"artificial":[37,58,85,120,130,141],"properties":[39,132],"could":[40],"be":[41,64],"effectively":[43],"regard.":[46],"We":[47,75,92],"investigate":[48,76],"such":[49],"a":[50],"case":[51],"impervious":[53,61,134,148],"surfaces.":[54,135,149],"Our":[55],"hypothesis":[56,78],"is:":[57],"surfaces":[62],"would":[63],"grey":[65],"because":[66],"its":[68],"spectral":[69],"blandness":[70],"over":[71],"350-2500":[72],"nm":[73],"range.":[74],"our":[77,126],"performing":[80],"chromatic":[81],"discrimination":[82],"analysis":[83],"using":[84],"variety":[88],"urban":[90],"use":[93],"field":[94],"spectra":[95,100,109],"recorded":[96],"spectrometer,":[98],"and":[99],"extracted":[101],"from":[102],"EO1-Hyperion":[103],"image.":[104],"Further,":[105],"we":[106],"filter":[107],"these":[108],"stretched":[111],"CIE":[112],"1964":[113],"matching":[115],"functions":[116],"provide":[118],"an":[119],"it.":[123],"Analysis":[124],"confirms":[125],"observations":[127],"about":[128],"Further":[136],"it":[137],"shows":[138],"potential":[139],"discriminate":[144],"sub":[145],"classes":[146]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
