{"id":"https://openalex.org/W7156752960","doi":"https://doi.org/10.48550/arxiv.2604.22886","title":"Breaking Degradation Coupling: A Structural Entropy Guided Decoupled Framework and Benchmark for Infrared Enhancement","display_name":"Breaking Degradation Coupling: A Structural Entropy Guided Decoupled Framework and Benchmark for Infrared Enhancement","publication_year":2026,"publication_date":"2026-04-24","ids":{"openalex":"https://openalex.org/W7156752960","doi":"https://doi.org/10.48550/arxiv.2604.22886"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.22886","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.22886","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.22886","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134777217","display_name":"Pu Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Pu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134765157","display_name":"Huafeng Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Huafeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134781662","display_name":"Yafei Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yafei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134808479","display_name":"Yu Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134760055","display_name":"Wen Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Wen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.7789999842643738,"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/T11019","display_name":"Image Enhancement Techniques","score":0.7789999842643738,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.09200000017881393,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.02239999920129776,"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/residual","display_name":"Residual","score":0.7116000056266785},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6478999853134155},{"id":"https://openalex.org/keywords/degradation","display_name":"Degradation (telecommunications)","score":0.5785999894142151},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5281999707221985},{"id":"https://openalex.org/keywords/decoupling","display_name":"Decoupling (probability)","score":0.5098000168800354},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.4864000082015991},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.429500013589859},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.38359999656677246},{"id":"https://openalex.org/keywords/high-fidelity","display_name":"High fidelity","score":0.37209999561309814}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7116000056266785},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6478999853134155},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6211000084877014},{"id":"https://openalex.org/C2779679103","wikidata":"https://www.wikidata.org/wiki/Q5251805","display_name":"Degradation (telecommunications)","level":2,"score":0.5785999894142151},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5281999707221985},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5175999999046326},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.5098000168800354},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.4864000082015991},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4325999915599823},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.429500013589859},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.38359999656677246},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.37209999561309814},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.3564000129699707},{"id":"https://openalex.org/C2984335091","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Thermal infrared","level":3,"score":0.3547999858856201},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3515999913215637},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.337799996137619},{"id":"https://openalex.org/C3020402766","wikidata":"https://www.wikidata.org/wiki/Q104376712","display_name":"Prior information","level":2,"score":0.3334999978542328},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.3240000009536743},{"id":"https://openalex.org/C204530211","wikidata":"https://www.wikidata.org/wiki/Q752823","display_name":"Thermal","level":2,"score":0.32339999079704285},{"id":"https://openalex.org/C2780799671","wikidata":"https://www.wikidata.org/wiki/Q17087362","display_name":"Transient (computer programming)","level":2,"score":0.31779998540878296},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30979999899864197},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.2915000021457672},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.28870001435279846},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.27619999647140503},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27090001106262207},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2567000091075897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.22886","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.22886","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.22886","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.22886","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Thermal":[0],"infrared":[1],"image":[2],"enhancement":[3],"aims":[4],"to":[5,22,116],"restore":[6],"high-quality":[7],"images":[8],"from":[9,121],"complex":[10],"compound":[11,50,108],"degradations.":[12],"Existing":[13],"all-in-one":[14],"approaches":[15],"typically":[16],"employ":[17],"a":[18,38,59,74,130,159],"single":[19],"shared":[20],"backbone":[21],"handle":[23,107],"diverse":[24],"degradations,":[25],"which":[26,84,122],"causes":[27],"gradient":[28],"interference":[29],"and":[30,55,96,139,147,153],"parameter":[31,86],"competition.":[32],"To":[33,106],"address":[34],"this,":[35],"we":[36],"propose":[37],"Structural":[39],"Entropy-Guided":[40],"Decoupled":[41],"(SEGD)":[42],"Framework.":[43],"Unlike":[44],"unified":[45],"modeling":[46],"paradigms,":[47],"SEGD":[48,150,173],"decomposes":[49],"degradations":[51],"into":[52],"independent":[53],"sub-processes":[54],"models":[56],"them":[57],"in":[58,113],"divide-and-conquer":[60,143],"manner":[61],"through":[62],"Degradation-Specific":[63],"Residual":[64],"Modules":[65],"(DRMs).":[66],"Each":[67],"DRM":[68,103],"focuses":[69],"on":[70],"residual":[71],"estimation":[72],"for":[73,163],"specific":[75],"degradation,":[76],"enabling":[77],"task":[78],"decoupling":[79],"while":[80,177],"remaining":[81],"jointly":[82],"trainable,":[83],"mitigates":[85],"contention.":[87],"A":[88],"Degradation-Aware":[89],"Evidential":[90],"Network":[91],"further":[92],"estimates":[93],"degradation":[94,140],"type":[95],"intensity,":[97],"providing":[98],"priors":[99],"that":[100,172],"adaptively":[101],"regulate":[102],"restoration":[104,119],"strength.":[105],"cases,":[109],"DRMs":[110],"are":[111,127],"composed":[112],"varying":[114],"orders":[115],"form":[117],"multiple":[118],"paths,":[120],"the":[123],"most":[124],"informative":[125],"features":[126],"aggregated":[128],"under":[129,165],"structural-entropy":[131],"criterion,":[132],"yielding":[133],"decoder-ready":[134],"representations":[135],"with":[136,181],"structural":[137],"fidelity":[138],"awareness.":[141],"Integrating":[142],"restoration,":[144],"evidential":[145],"perception,":[146],"entropy-guided":[148],"adaptation,":[149],"achieves":[151],"fine-grained":[152],"interpretable":[154],"enhancement.":[155],"We":[156],"also":[157],"construct":[158],"nighttime":[160],"TIR":[161],"benchmark":[162],"evaluation":[164],"real":[166],"low-light":[167],"conditions.":[168],"Experimental":[169],"results":[170],"demonstrate":[171],"surpasses":[174],"state-of-the-art":[175],"methods":[176],"achieving":[178],"higher":[179],"efficiency":[180],"fewer":[182],"parameters.":[183]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-29T00:00:00"}
