{"id":"https://openalex.org/W4379116708","doi":"https://doi.org/10.1109/tgrs.2023.3282186","title":"Hyperspectral Image Compression via Cross-Channel Contrastive Learning","display_name":"Hyperspectral Image Compression via Cross-Channel Contrastive Learning","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4379116708","doi":"https://doi.org/10.1109/tgrs.2023.3282186"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3282186","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3282186","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-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/A5102782499","display_name":"Yuanyuan Guo","orcid":"https://orcid.org/0000-0002-0223-9037"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanyuan Guo","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-0223-9037","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747","https://openalex.org/I4210118728"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036258937","display_name":"Yanwen Chong","orcid":"https://orcid.org/0000-0002-7944-8515"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanwen Chong","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-7944-8515","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747","https://openalex.org/I4210118728"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049671371","display_name":"Shaoming Pan","orcid":"https://orcid.org/0000-0001-6789-3876"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaoming Pan","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-6789-3876","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747","https://openalex.org/I4210118728"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3447,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.89823847,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9995999932289124,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9991999864578247,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9991999864578247,"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/discriminative-model","display_name":"Discriminative model","score":0.8587954044342041},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7979615926742554},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7826876640319824},{"id":"https://openalex.org/keywords/lossy-compression","display_name":"Lossy compression","score":0.7050037980079651},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6866034269332886},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6247678399085999},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5408104062080383},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.5200766921043396},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.48587483167648315},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.4816807210445404},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44810739159584045},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4444698691368103},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.4438786804676056},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.44073486328125},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.43315237760543823},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29478365182876587},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.16797208786010742}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8587954044342041},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7979615926742554},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7826876640319824},{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.7050037980079651},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6866034269332886},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6247678399085999},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5408104062080383},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.5200766921043396},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.48587483167648315},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.4816807210445404},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44810739159584045},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4444698691368103},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.4438786804676056},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.44073486328125},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.43315237760543823},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29478365182876587},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.16797208786010742},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3282186","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3282186","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G616159729","display_name":null,"funder_award_id":"62072345","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8975931662","display_name":"\u7528\u6237\u8bbf\u95ee\u9a71\u52a8\u7684\u7a7a\u95f4\u6570\u636e\u5b58\u50a8\u7ec4\u7ec7\u4e0e\u670d\u52a1\u65b9\u6cd5\u7814\u7a76","funder_award_id":"41671382","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326938","display_name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing","ror":"https://ror.org/02bpap860"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W1580389772","https://openalex.org/W1995875735","https://openalex.org/W2005083749","https://openalex.org/W2010319424","https://openalex.org/W2012946078","https://openalex.org/W2015415108","https://openalex.org/W2100109944","https://openalex.org/W2119047110","https://openalex.org/W2127308700","https://openalex.org/W2133764833","https://openalex.org/W2142458747","https://openalex.org/W2152061763","https://openalex.org/W2153922636","https://openalex.org/W2158548804","https://openalex.org/W2163922914","https://openalex.org/W2519420704","https://openalex.org/W2531452236","https://openalex.org/W2534320940","https://openalex.org/W2552465432","https://openalex.org/W2785562966","https://openalex.org/W2798991696","https://openalex.org/W2842511635","https://openalex.org/W2869998349","https://openalex.org/W2899937451","https://openalex.org/W2901973422","https://openalex.org/W2912003885","https://openalex.org/W2949361041","https://openalex.org/W2960241714","https://openalex.org/W2962676454","https://openalex.org/W2963149687","https://openalex.org/W2964098744","https://openalex.org/W2991616716","https://openalex.org/W3005680577","https://openalex.org/W3025440211","https://openalex.org/W3034469748","https://openalex.org/W3035524453","https://openalex.org/W3036682213","https://openalex.org/W3100975431","https://openalex.org/W3102189958","https://openalex.org/W3102507295","https://openalex.org/W3102745911","https://openalex.org/W3108655343","https://openalex.org/W3141915823","https://openalex.org/W3145049705","https://openalex.org/W3163432535","https://openalex.org/W3173269149","https://openalex.org/W3175457126","https://openalex.org/W3179626733","https://openalex.org/W3200799048","https://openalex.org/W3208382921","https://openalex.org/W4281257095","https://openalex.org/W4285821234","https://openalex.org/W4297659253","https://openalex.org/W4297808394","https://openalex.org/W4391799317","https://openalex.org/W6694251005","https://openalex.org/W6754634825","https://openalex.org/W6774314701","https://openalex.org/W6780365925","https://openalex.org/W6798132488","https://openalex.org/W6798322722"],"related_works":["https://openalex.org/W3210332869","https://openalex.org/W4210785996","https://openalex.org/W4327499886","https://openalex.org/W2181436147","https://openalex.org/W1680283075","https://openalex.org/W3162084246","https://openalex.org/W2056051076","https://openalex.org/W2793856282","https://openalex.org/W2015677580","https://openalex.org/W2115343698"],"abstract_inverted_index":{"In":[0,74,136],"recent":[1],"years,":[2],"advances":[3],"in":[4,48,51,57,128],"deep":[5],"learning":[6,86],"have":[7],"greatly":[8],"promoted":[9],"the":[10,117,122,125,137,152,167,179,197],"development":[11],"of":[12,139,178],"hyperspectral":[13,81],"image":[14],"(HSI)":[15],"compression":[16,21,59,72,82,173],"algorithms.":[17],"However,":[18],"most":[19],"existing":[20],"approaches":[22],"directly":[23],"rely":[24],"on":[25,160,196],"rate-distortion":[26],"optimization":[27],"without":[28],"other":[29],"guidance":[30],"during":[31],"model":[32],"learning.":[33],"Therefore,":[34],"this":[35,75],"brings":[36],"challenges":[37],"to":[38,88,110,132,150,190],"distinguishing":[39],"similar":[40],"features":[41],"or":[42],"objects":[43],"that":[44,166],"are":[45],"widely":[46],"available":[47],"HSIs,":[49],"especially":[50],"remote":[52],"sensing":[53],"scenes,":[54],"since":[55],"quantification":[56],"lossy":[58],"can":[60,170],"cause":[61],"informative":[62,95,106],"attribute":[63,134,140],"(e.g.,":[64],"category)":[65],"collapse":[66],"and":[67,93,112],"loss":[68],"problems":[69],"at":[70],"high":[71],"ratios.":[73],"paper,":[76],"we":[77,102,142],"propose":[78],"a":[79,104,144],"novel":[80],"network":[83],"via":[84,155],"contrastive":[85,105,145,156],"(HCCNet)":[87],"help":[89],"generate":[90],"discriminative":[91,114],"representations":[92],"preserve":[94],"attributes":[96,115,154],"as":[97,99,176],"much":[98],"possible.":[100],"Specifically,":[101],"design":[103],"feature":[107,147,157],"encoding":[108],"(CIFE)":[109],"extract":[111],"organize":[113],"from":[116,184],"original":[118],"HSIs":[119],"by":[120],"enlarging":[121],"discrimination":[123],"over":[124],"learned":[126],"latents":[127],"different":[129,162],"channel":[130],"indexes":[131],"relieve":[133],"collapses.":[135],"case":[138],"losses,":[141],"define":[143],"invariant":[146],"recovery":[148],"(CIFR)":[149],"discover":[151],"lost":[153],"refinement.":[158],"Experiments":[159],"five":[161],"HSI":[163],"datasets":[164],"illustrate":[165],"proposed":[168],"HCCNet":[169],"achieve":[171],"impressive":[172],"performance,":[174],"such":[175],"improvement":[177],"peak":[180],"signal-to-noise":[181],"ratio":[182],"(PSNR)":[183],"28.86":[185],"dB":[186,192],"(at":[187,193],"0.2284":[188],"bpppb)":[189,195],"30.30":[191],"0.1960":[194],"Chikusei":[198],"dataset.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
