{"id":"https://openalex.org/W2024465750","doi":"https://doi.org/10.1109/igarss.2007.4424018","title":"A new method for quality assessment of hyperspectral images","display_name":"A new method for quality assessment of hyperspectral images","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W2024465750","doi":"https://doi.org/10.1109/igarss.2007.4424018","mag":"2024465750"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2007.4424018","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2007.4424018","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"article","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/A5058002875","display_name":"Andrea Garzelli","orcid":"https://orcid.org/0000-0003-2332-780X"},"institutions":[{"id":"https://openalex.org/I102064193","display_name":"University of Siena","ror":"https://ror.org/01tevnk56","country_code":"IT","type":"education","lineage":["https://openalex.org/I102064193"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Andrea Garzelli","raw_affiliation_strings":["DII-Univ. of Siena, Siena, Italy","DII-Univ. of Siena, Siena"],"affiliations":[{"raw_affiliation_string":"DII-Univ. of Siena, Siena, Italy","institution_ids":["https://openalex.org/I102064193"]},{"raw_affiliation_string":"DII-Univ. of Siena, Siena","institution_ids":["https://openalex.org/I102064193"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042160082","display_name":"Filippo Nencini","orcid":null},"institutions":[{"id":"https://openalex.org/I102064193","display_name":"University of Siena","ror":"https://ror.org/01tevnk56","country_code":"IT","type":"education","lineage":["https://openalex.org/I102064193"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Filippo Nencini","raw_affiliation_strings":["DII-Univ. of Siena, Siena, Italy","DII-Univ. of Siena, Siena"],"affiliations":[{"raw_affiliation_string":"DII-Univ. of Siena, Siena, Italy","institution_ids":["https://openalex.org/I102064193"]},{"raw_affiliation_string":"DII-Univ. of Siena, Siena","institution_ids":["https://openalex.org/I102064193"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052624884","display_name":"Luciano Alparone","orcid":"https://orcid.org/0000-0002-8984-938X"},"institutions":[{"id":"https://openalex.org/I45084792","display_name":"University of Florence","ror":"https://ror.org/04jr1s763","country_code":"IT","type":"education","lineage":["https://openalex.org/I45084792"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luciano Alparone","raw_affiliation_strings":["DET-Univ. of Florence, Florence, Italy","DET-Univ. of Florence, Florence"],"affiliations":[{"raw_affiliation_string":"DET-Univ. of Florence, Florence, Italy","institution_ids":["https://openalex.org/I45084792"]},{"raw_affiliation_string":"DET-Univ. of Florence, Florence","institution_ids":["https://openalex.org/I45084792"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061007254","display_name":"Stefano Baronti","orcid":"https://orcid.org/0000-0003-0492-0886"},"institutions":[{"id":"https://openalex.org/I4210092323","display_name":"Nello Carrara Institute of Applied Physics","ror":"https://ror.org/00dqega85","country_code":"IT","type":"facility","lineage":["https://openalex.org/I4210092323","https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Stefano Baronti","raw_affiliation_strings":["IFAC-CNR, S.to F.no (FI), Italy","IFAC-CNR, Florence"],"affiliations":[{"raw_affiliation_string":"IFAC-CNR, S.to F.no (FI), Italy","institution_ids":["https://openalex.org/I4210092323"]},{"raw_affiliation_string":"IFAC-CNR, Florence","institution_ids":["https://openalex.org/I4210092323"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5058002875"],"corresponding_institution_ids":["https://openalex.org/I102064193"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.15187587,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"63","issue":null,"first_page":"5138","last_page":"5141"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":1.0,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":1.0,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9987999796867371,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9947999715805054,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/panchromatic-film","display_name":"Panchromatic film","score":0.9525418281555176},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9262638092041016},{"id":"https://openalex.org/keywords/hypercomplex-number","display_name":"Hypercomplex number","score":0.7239946722984314},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.6421139240264893},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6178479790687561},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5352811217308044},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.5042177438735962},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4930083453655243},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.4675655961036682},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.45456838607788086},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.45433124899864197},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.447933554649353},{"id":"https://openalex.org/keywords/quality-assessment","display_name":"Quality assessment","score":0.4105328917503357},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39522308111190796},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.38152241706848145},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.36569422483444214},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2972784638404846},{"id":"https://openalex.org/keywords/evaluation-methods","display_name":"Evaluation methods","score":0.1434515118598938},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12850835919380188},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07388046383857727}],"concepts":[{"id":"https://openalex.org/C107445234","wikidata":"https://www.wikidata.org/wiki/Q280995","display_name":"Panchromatic film","level":3,"score":0.9525418281555176},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9262638092041016},{"id":"https://openalex.org/C203249530","wikidata":"https://www.wikidata.org/wiki/Q837414","display_name":"Hypercomplex number","level":3,"score":0.7239946722984314},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.6421139240264893},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6178479790687561},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5352811217308044},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.5042177438735962},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4930083453655243},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.4675655961036682},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.45456838607788086},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.45433124899864197},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.447933554649353},{"id":"https://openalex.org/C3020001037","wikidata":"https://www.wikidata.org/wiki/Q836575","display_name":"Quality assessment","level":3,"score":0.4105328917503357},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39522308111190796},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38152241706848145},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.36569422483444214},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2972784638404846},{"id":"https://openalex.org/C3018395757","wikidata":"https://www.wikidata.org/wiki/Q1379672","display_name":"Evaluation methods","level":2,"score":0.1434515118598938},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12850835919380188},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07388046383857727},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C200127275","wikidata":"https://www.wikidata.org/wiki/Q173853","display_name":"Quaternion","level":2,"score":0.0},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/igarss.2007.4424018","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2007.4424018","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:flore.unifi.it:2158/781854","is_oa":false,"landing_page_url":"http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4424018","pdf_url":null,"source":{"id":"https://openalex.org/S4306402033","display_name":"Florence Research (University of Florence)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I45084792","host_organization_name":"University of Florence","host_organization_lineage":["https://openalex.org/I45084792"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:usiena-air.unisi.it:11365/5193","is_oa":false,"landing_page_url":"http://hdl.handle.net/11365/5193","pdf_url":null,"source":{"id":"https://openalex.org/S4377196319","display_name":"Use Siena air (University of Siena)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I102064193","host_organization_name":"University of Siena","host_organization_lineage":["https://openalex.org/I102064193"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1553305639","https://openalex.org/W2020442368","https://openalex.org/W2068474295","https://openalex.org/W2088538848","https://openalex.org/W2123046940","https://openalex.org/W2124743705","https://openalex.org/W2141565698","https://openalex.org/W2159269332","https://openalex.org/W2163334907","https://openalex.org/W2171845746","https://openalex.org/W4251471643","https://openalex.org/W6633088995","https://openalex.org/W6685078114"],"related_works":["https://openalex.org/W2388558253","https://openalex.org/W2385264142","https://openalex.org/W2044102280","https://openalex.org/W2380263558","https://openalex.org/W2992121921","https://openalex.org/W1966079689","https://openalex.org/W1954408549","https://openalex.org/W2418010961","https://openalex.org/W2108591609","https://openalex.org/W2909977981"],"abstract_inverted_index":{"This":[0],"work":[1],"focuses":[2],"on":[3,75],"quality":[4],"assessment":[5],"of":[6,8,30],"fusion":[7,48],"hyperspectral":[9],"(HS)":[10],"images":[11,24],"with":[12],"high-resolution":[13],"panchromatic":[14],"(Pan)":[15],"data.":[16],"A":[17],"novel":[18],"fidelity":[19],"index":[20],"suitable":[21],"for":[22,67],"HS":[23,63],"is":[25],"defined":[26],"from":[27,55],"the":[28,56,61],"theory":[29],"hypercomplex":[31],"numbers":[32],"(2(n)-ons).":[33],"Both":[34],"spectral":[35],"and":[36,69,77],"spatial":[37],"distortion":[38],"measurements":[39],"are":[40,65,73],"encapsulated":[41],"in":[42],"a":[43],"unique":[44],"score":[45],"index.":[46],"Some":[47],"methods":[49],"capable":[50],"to":[51,60],"selectively":[52],"inject":[53],"spatial-frequencies":[54],"higher-resolution":[57],"Pan":[58],"image":[59],"coarser":[62],"bands":[64],"used":[66],"testing":[68],"comparisons.":[70],"Experimental":[71],"results":[72],"presented":[74],"Hyperion":[76],"ALI":[78],"data":[79],"sets.":[80]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2016-06-24T00:00:00"}
