{"id":"https://openalex.org/W7155980051","doi":"https://doi.org/10.48550/arxiv.2604.22093","title":"FLARE-BO: Fused Luminance and Adaptive Retinex Enhancement via Bayesian Optimisation for Low-Light Robotic Vision","display_name":"FLARE-BO: Fused Luminance and Adaptive Retinex Enhancement via Bayesian Optimisation for Low-Light Robotic Vision","publication_year":2026,"publication_date":"2026-04-23","ids":{"openalex":"https://openalex.org/W7155980051","doi":"https://doi.org/10.48550/arxiv.2604.22093"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.22093","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.22093","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.22093","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134675488","display_name":"Nathan Shankar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shankar, Nathan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023634954","display_name":"Pawe\u0142 \u0141adosz","orcid":"https://orcid.org/0000-0002-1154-8333"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ladosz, Pawel","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5055149475","display_name":"Hujun Yin","orcid":"https://orcid.org/0000-0002-9198-5401"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yin, Hujun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"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":0.7330999970436096,"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":0.7330999970436096,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.10040000081062317,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.020500000566244125,"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/color-constancy","display_name":"Color constancy","score":0.7185999751091003},{"id":"https://openalex.org/keywords/luminance","display_name":"Luminance","score":0.6486999988555908},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.521399974822998},{"id":"https://openalex.org/keywords/color-balance","display_name":"Color balance","score":0.429500013589859},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.4099999964237213},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3368000090122223},{"id":"https://openalex.org/keywords/chrominance","display_name":"Chrominance","score":0.33149999380111694},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.3197000026702881},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.31619998812675476}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7800999879837036},{"id":"https://openalex.org/C187888035","wikidata":"https://www.wikidata.org/wiki/Q2563885","display_name":"Color constancy","level":3,"score":0.7185999751091003},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6597999930381775},{"id":"https://openalex.org/C73313986","wikidata":"https://www.wikidata.org/wiki/Q355386","display_name":"Luminance","level":2,"score":0.6486999988555908},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6238999962806702},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.521399974822998},{"id":"https://openalex.org/C159784718","wikidata":"https://www.wikidata.org/wiki/Q182571","display_name":"Color balance","level":5,"score":0.429500013589859},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.4099999964237213},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3368000090122223},{"id":"https://openalex.org/C163204269","wikidata":"https://www.wikidata.org/wiki/Q355263","display_name":"Chrominance","level":3,"score":0.33149999380111694},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.31619998812675476},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3156999945640564},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.30959999561309814},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3052999973297119},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.2969000041484833},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C17916492","wikidata":"https://www.wikidata.org/wiki/Q1144257","display_name":"Gamma correction","level":3,"score":0.28850001096725464},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.28690001368522644},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.2770000100135803},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.262800008058548},{"id":"https://openalex.org/C14740026","wikidata":"https://www.wikidata.org/wiki/Q1136665","display_name":"Vignetting","level":3,"score":0.26179999113082886}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.22093","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.22093","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.22093","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.22093","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":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Reliable":[0],"visual":[1],"perception":[2],"under":[3,84],"low":[4],"illumination":[5,66,113],"remains":[6],"a":[7,46,133],"core":[8],"challenge":[9],"for":[10,148],"autonomous":[11],"robotic":[12],"systems,":[13],"where":[14],"degraded":[15],"image":[16],"quality":[17],"directly":[18],"compromises":[19],"navigation,":[20],"inspection,":[21],"and":[22,42,72,93,125,143,169],"various":[23],"operations.":[24],"A":[25],"recent":[26],"training":[27],"free":[28],"approach":[29],"showed":[30],"that":[31,57,103,181],"Bayesian":[32,98],"optimisation":[33],"with":[34],"Gaussian":[35],"Processes":[36],"can":[37],"adaptively":[38],"select":[39],"brightness,":[40],"contrast,":[41],"denoising":[43],"parameters":[44,107],"on":[45,74],"per-image":[47],"basis,":[48],"achieving":[49],"competitive":[50],"enhancement":[51],"without":[52],"any":[53],"learned":[54],"model.":[55],"However,":[56],"framework":[58,102],"is":[59,160],"limited":[60],"to":[61,80],"three":[62],"parameters,":[63],"applies":[64],"no":[65],"decomposition":[67],"or":[68],"white":[69,123],"balance":[70],"correction,":[71,111],"relies":[73],"Non-Local":[75],"Means":[76],"denoising,":[77,116,120],"which":[78],"tends":[79],"over":[81,178],"smooth":[82],"edges":[83],"noisy":[85],"conditions.":[86],"This":[87],"paper":[88],"proposes":[89],"FLARE-BO":[90],"(Fused":[91],"Luminance":[92],"Adaptive":[94],"Retinex":[95],"Enhancement":[96],"via":[97],"Optimisation),":[99],"an":[100],"extended":[101],"jointly":[104],"optimises":[105],"eight":[106],"spanning":[108],"across":[109],"gamma":[110],"LIME-style":[112],"normalisation,":[114,137],"chrominance":[115],"bilateral":[117],"filtering,":[118],"NLM":[119],"Grey-World":[121],"automatic":[122],"balance,":[124],"adaptive":[126],"post":[127],"smoothing.":[128],"The":[129],"search":[130],"engine":[131],"employs":[132],"unit":[134],"hypercube":[135],"parameter":[136],"objective":[138],"standardisation,":[139],"Sobol":[140],"quasi-random":[141],"initialisation,":[142],"Log":[144],"Expected":[145],"Improvement":[146],"acquisition":[147],"principled":[149],"exploration":[150],"of":[151,156,174],"the":[152,157,163,175],"expanded":[153],"space.":[154],"Performance":[155],"proposed":[158,176],"method":[159,177],"benchmarked":[161],"using":[162,186],"Low":[164],"Light":[165],"paired":[166],"dataset":[167],"(LOL)":[168],"results":[170],"show":[171],"marked":[172],"improvements":[173],"existing":[179],"methods":[180],"were":[182],"not":[183],"specifically":[184],"trained":[185],"this":[187],"dataset.":[188]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-28T00:00:00"}
