{"id":"https://openalex.org/W2063618284","doi":"https://doi.org/10.1109/igarss.2015.7326963","title":"Lossy compression of hyperspectral images optimizing spectral unmixing","display_name":"Lossy compression of hyperspectral images optimizing spectral unmixing","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W2063618284","doi":"https://doi.org/10.1109/igarss.2015.7326963","mag":"2063618284"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2015.7326963","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2015.7326963","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","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/A5046045649","display_name":"Azam Karami","orcid":"https://orcid.org/0000-0002-9820-4217"},"institutions":[{"id":"https://openalex.org/I115566878","display_name":"Shahid Bahonar University of Kerman","ror":"https://ror.org/04zn42r77","country_code":"IR","type":"education","lineage":["https://openalex.org/I115566878"]},{"id":"https://openalex.org/I149213910","display_name":"University of Antwerp","ror":"https://ror.org/008x57b05","country_code":"BE","type":"education","lineage":["https://openalex.org/I149213910"]}],"countries":["BE","IR"],"is_corresponding":false,"raw_author_name":"Azam Karami","raw_affiliation_strings":["Department of Electrical Engineering, Shahid Bahonar, University of Kerman, Kerman, Iran","Minds-Visionlab, University of Antwerp, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Shahid Bahonar, University of Kerman, Kerman, Iran","institution_ids":["https://openalex.org/I115566878"]},{"raw_affiliation_string":"Minds-Visionlab, University of Antwerp, Belgium","institution_ids":["https://openalex.org/I149213910"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048918209","display_name":"Rob Heylen","orcid":"https://orcid.org/0000-0002-8341-9397"},"institutions":[{"id":"https://openalex.org/I149213910","display_name":"University of Antwerp","ror":"https://ror.org/008x57b05","country_code":"BE","type":"education","lineage":["https://openalex.org/I149213910"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Rob Heylen","raw_affiliation_strings":["Minds-Visionlab, University of Antwerp, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Minds-Visionlab, University of Antwerp, Belgium","institution_ids":["https://openalex.org/I149213910"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009310543","display_name":"Paul Scheunders","orcid":"https://orcid.org/0000-0003-2447-4772"},"institutions":[{"id":"https://openalex.org/I149213910","display_name":"University of Antwerp","ror":"https://ror.org/008x57b05","country_code":"BE","type":"education","lineage":["https://openalex.org/I149213910"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Paul Scheunders","raw_affiliation_strings":["Minds-Visionlab, University of Antwerp, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Minds-Visionlab, University of Antwerp, Belgium","institution_ids":["https://openalex.org/I149213910"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5031","last_page":"5034"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994000196456909,"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":0.9994000196456909,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9973999857902527,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/lossy-compression","display_name":"Lossy compression","score":0.8462870121002197},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7759045362472534},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.6935197710990906},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.5920346975326538},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5705839395523071},{"id":"https://openalex.org/keywords/compression-ratio","display_name":"Compression ratio","score":0.541641116142273},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5359874963760376},{"id":"https://openalex.org/keywords/jpeg-2000","display_name":"JPEG 2000","score":0.5205329656600952},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.5203642249107361},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4877382218837738},{"id":"https://openalex.org/keywords/peak-signal-to-noise-ratio","display_name":"Peak signal-to-noise ratio","score":0.4623801112174988},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.45826464891433716},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.4537430703639984},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.4321081042289734},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35620367527008057},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3310743272304535},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3231039047241211},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.25731703639030457},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.17435398697853088},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09119141101837158},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.084413081407547}],"concepts":[{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.8462870121002197},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7759045362472534},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6935197710990906},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.5920346975326538},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5705839395523071},{"id":"https://openalex.org/C25797200","wikidata":"https://www.wikidata.org/wiki/Q828137","display_name":"Compression ratio","level":3,"score":0.541641116142273},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5359874963760376},{"id":"https://openalex.org/C69216139","wikidata":"https://www.wikidata.org/wiki/Q931783","display_name":"JPEG 2000","level":5,"score":0.5205329656600952},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.5203642249107361},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4877382218837738},{"id":"https://openalex.org/C154579607","wikidata":"https://www.wikidata.org/wiki/Q3373850","display_name":"Peak signal-to-noise ratio","level":3,"score":0.4623801112174988},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.45826464891433716},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.4537430703639984},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.4321081042289734},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35620367527008057},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3310743272304535},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3231039047241211},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25731703639030457},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.17435398697853088},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09119141101837158},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.084413081407547},{"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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C511840579","wikidata":"https://www.wikidata.org/wiki/Q12757","display_name":"Internal combustion engine","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2015.7326963","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2015.7326963","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1246381107","https://openalex.org/W1513817866","https://openalex.org/W2002652706","https://openalex.org/W2103782255","https://openalex.org/W2113753426","https://openalex.org/W2157321686","https://openalex.org/W2158548804","https://openalex.org/W2169245194","https://openalex.org/W2170407643"],"related_works":["https://openalex.org/W2013943429","https://openalex.org/W3210332869","https://openalex.org/W3212420620","https://openalex.org/W4307097729","https://openalex.org/W4210785996","https://openalex.org/W4327499886","https://openalex.org/W3080614128","https://openalex.org/W2569922886","https://openalex.org/W3112580190","https://openalex.org/W2738855305"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"a":[5,30,35,95,123],"new":[6],"hyperspectral":[7],"image":[8],"lossy":[9,112],"compression":[10,56,113],"method":[11,147],"that":[12,104,142],"aims":[13],"to":[14,129,140],"optimally":[15],"compress":[16],"in":[17,108],"both":[18],"spatial":[19],"and":[20,23,78,118,126],"spectral":[21,27,86],"domains":[22],"simultaneously":[24],"considers":[25],"linear":[26],"unmixing":[28],"as":[29,116,151],"target.":[31],"To":[32],"achieve":[33],"this,":[34],"non-negative":[36],"tucker":[37],"decomposition":[38],"is":[39,92,138],"applied.":[40],"This":[41],"algorithm":[42],"has":[43],"three":[44],"flexible":[45],"dimension":[46],"parameters.":[47],"We":[48],"propose":[49],"an":[50],"approach":[51],"that,":[52],"for":[53,133],"any":[54,134],"desired":[55],"ratio":[57,131],"(CR),":[58],"chooses":[59],"the":[60,65,72,76,105,143,152],"optimal":[61],"parameters":[62],"by":[63,94],"minimizing":[64],"root":[66],"mean":[67],"square":[68,85],"error":[69],"(RMSE)":[70],"between":[71],"abundance":[73],"matrices":[74],"of":[75,145,154],"original":[77],"compressed":[79],"datasets":[80],"using":[81],"fully":[82],"constrained":[83],"least":[84],"unmixing.":[87],"The":[88],"resulting":[89],"optimization":[90],"problem":[91],"solved":[93],"Particle":[96],"Swarm":[97],"Optimization":[98],"algorithm.":[99],"Our":[100],"simulation":[101],"results":[102],"show":[103],"proposed":[106],"method,":[107],"comparison":[109],"with":[110],"well-known":[111],"methods":[114],"such":[115],"3D-SPECK":[117],"combined":[119],"PCA+JPEG2000":[120],"algorithms,":[121],"provides":[122],"lower":[124],"RMSE":[125],"higher":[127],"signal":[128],"noise":[130],"(SNR)":[132],"given":[135],"CR.":[136],"It":[137],"noteworthy":[139],"mention":[141],"superiority":[144],"our":[146],"becomes":[148],"more":[149],"apparent":[150],"value":[153],"CR":[155],"grows.":[156]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}