{"id":"https://openalex.org/W4408564651","doi":"https://doi.org/10.1109/jstars.2025.3550721","title":"Lossless Compression Framework Using Lossy Prior for High-Resolution Remote Sensing Images","display_name":"Lossless Compression Framework Using Lossy Prior for High-Resolution Remote Sensing Images","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4408564651","doi":"https://doi.org/10.1109/jstars.2025.3550721"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2025.3550721","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3550721","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/jstars.2025.3550721","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113385171","display_name":"Enjia Gu","orcid":null},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Enjia Gu","raw_affiliation_strings":["School of Computer Science, China University of Geosciences, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038549098","display_name":"Yongshan Zhang","orcid":"https://orcid.org/0000-0001-5817-1732"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongshan Zhang","raw_affiliation_strings":["School of Computer Science, China University of Geosciences, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-5817-1732","affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102218959","display_name":"Xinxin Wang","orcid":"https://orcid.org/0009-0000-6065-7651"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Xinxin Wang","raw_affiliation_strings":["Department of Computer and Information Science, University of Macau, Macau, China"],"raw_orcid":"https://orcid.org/0009-0000-6065-7651","affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, University of Macau, Macau, China","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078539725","display_name":"Xinwei Jiang","orcid":"https://orcid.org/0000-0001-6783-2176"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinwei Jiang","raw_affiliation_strings":["School of Computer Science, China University of Geosciences, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-6783-2176","affiliations":[{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":2.2966,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.87414109,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"18","issue":null,"first_page":"8590","last_page":"8601"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9987999796867371,"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":0.9987999796867371,"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":0.9818999767303467,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9223999977111816,"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/lossy-compression","display_name":"Lossy compression","score":0.9073827266693115},{"id":"https://openalex.org/keywords/lossless-compression","display_name":"Lossless compression","score":0.7929428815841675},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6904270052909851},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.5370840430259705},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.49770739674568176},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.46178844571113586},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4232228994369507},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3733915090560913},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1743096113204956},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.09835758805274963}],"concepts":[{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.9073827266693115},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.7929428815841675},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6904270052909851},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.5370840430259705},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.49770739674568176},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46178844571113586},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4232228994369507},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3733915090560913},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1743096113204956},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.09835758805274963},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2025.3550721","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3550721","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:119f629af0e841a39c3f7e69092d1a37","is_oa":true,"landing_page_url":"https://doaj.org/article/119f629af0e841a39c3f7e69092d1a37","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 8590-8601 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2025.3550721","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3550721","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7304422909","display_name":null,"funder_award_id":"62106241","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W1877865836","https://openalex.org/W1998497852","https://openalex.org/W2103027412","https://openalex.org/W2393988244","https://openalex.org/W2965631471","https://openalex.org/W2971904947","https://openalex.org/W3037595032","https://openalex.org/W3089039599","https://openalex.org/W3093896170","https://openalex.org/W3133953507","https://openalex.org/W3175457126","https://openalex.org/W4294310684","https://openalex.org/W4312348190","https://openalex.org/W4320027769","https://openalex.org/W4366773133","https://openalex.org/W4375929061","https://openalex.org/W4376464564","https://openalex.org/W4378083663","https://openalex.org/W4379107763","https://openalex.org/W4382998692","https://openalex.org/W4385483181","https://openalex.org/W4387449305","https://openalex.org/W4389396271","https://openalex.org/W4390045336","https://openalex.org/W4390480875","https://openalex.org/W4391109953","https://openalex.org/W4392404248","https://openalex.org/W4392542361","https://openalex.org/W4394565015","https://openalex.org/W4396528656","https://openalex.org/W4399801011","https://openalex.org/W4400275877","https://openalex.org/W4401726115","https://openalex.org/W4402570051","https://openalex.org/W4402674181","https://openalex.org/W4403277031","https://openalex.org/W4403780815","https://openalex.org/W4404101607","https://openalex.org/W6799260705","https://openalex.org/W6843772381"],"related_works":["https://openalex.org/W2385628723","https://openalex.org/W2547124190","https://openalex.org/W3180760233","https://openalex.org/W3035703949","https://openalex.org/W4247601675","https://openalex.org/W1970394887","https://openalex.org/W755971114","https://openalex.org/W2118338613","https://openalex.org/W1982468865","https://openalex.org/W4210455546"],"abstract_inverted_index":{"Lossless":[0],"compression":[1,26,35,39,49,55,63,100,111,172,192,202,210],"of":[2,18,101,138,159,170,186,197],"remote":[3,76,177],"sensing":[4,77,178],"images":[5],"is":[6,132],"critically":[7],"important":[8],"for":[9,97],"minimizing":[10],"storage":[11],"requirements":[12],"while":[13],"preserving":[14],"the":[15,19,62,74,99,155,166,171,182,187],"complete":[16],"integrity":[17],"data.":[20],"The":[21,82,129],"main":[22,83],"challenge":[23],"in":[24,28,125],"lossless":[25,48,110,191],"lies":[27],"striking":[29],"a":[30,68,89,126,143,148,195],"good":[31],"balance":[32],"between":[33],"reasonable":[34],"durations":[36],"and":[37,122,147,168,184,190,204],"high":[38],"ratios.":[40],"In":[41],"this":[42],"article,":[43],"we":[44],"introduce":[45],"an":[46,133,139],"innovative":[47],"framework":[50,66],"that":[51],"uniquely":[52],"utilizes":[53],"lossy":[54,91,116],"data":[56],"as":[57],"prior":[58,95,117],"knowledge":[59,96],"to":[60,72,93,109,153],"enhance":[61],"process.":[64,173],"Our":[65],"employs":[67],"checkerboard":[69],"segmentation":[70],"technique":[71],"divides":[73],"original":[75],"image":[78,140,179],"into":[79],"various":[80],"subimages.":[81,103],"diagonal":[84],"subimages":[85,105],"are":[86,106],"compressed":[87],"using":[88,112],"traditional":[90,201],"method":[92],"obtain":[94],"facilitating":[98],"all":[102],"These":[104],"then":[107],"subjected":[108],"our":[113],"newly":[114],"developed":[115],"probability":[118,150,157],"prediction":[119],"network":[120,135],"(LP3Net)":[121],"arithmetic":[123],"coding":[124],"specific":[127],"order.":[128],"proposed":[130,188],"LP3Net":[131,189],"advanced":[134],"architecture,":[136],"consisting":[137],"preprocessing":[141],"module,":[142,146,152],"channel":[144],"enhancement":[145],"pixel":[149,161],"transformer":[151],"learn":[154],"discrete":[156],"distribution":[158],"each":[160],"within":[162],"every":[163],"subimage,":[164],"enhancing":[165],"accuracy":[167],"efficiency":[169,185],"Experiments":[174],"on":[175],"high-resolution":[176],"datasets":[180],"demonstrate":[181],"effectiveness":[183],"framework,":[193],"achieving":[194],"minimum":[196],"4.57%":[198],"improvement":[199,206],"over":[200,207],"methods":[203],"1.86%":[205],"deep":[208],"learning-based":[209],"methods.":[211]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}
