{"id":"https://openalex.org/W7131239332","doi":"https://doi.org/10.1109/vcip67698.2025.11396892","title":"Low-Light Image Enhancement Based on Intrinsic Image Decomposition","display_name":"Low-Light Image Enhancement Based on Intrinsic Image Decomposition","publication_year":2025,"publication_date":"2025-12-01","ids":{"openalex":"https://openalex.org/W7131239332","doi":"https://doi.org/10.1109/vcip67698.2025.11396892"},"language":null,"primary_location":{"id":"doi:10.1109/vcip67698.2025.11396892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip67698.2025.11396892","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5078715565","display_name":"Diclehan Ulucan","orcid":"https://orcid.org/0000-0002-7059-302X"},"institutions":[{"id":"https://openalex.org/I2799318839","display_name":"Universit\u00e4tsmedizin Greifswald","ror":"https://ror.org/025vngs54","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I2799318839"]},{"id":"https://openalex.org/I36522303","display_name":"Universit\u00e4t Greifswald","ror":"https://ror.org/00r1edq15","country_code":"DE","type":"education","lineage":["https://openalex.org/I36522303"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Diclehan Ulucan","raw_affiliation_strings":["University of Greifswald, Institute of Mathematics and Computer Science,Greifswald,Germany,17489"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Greifswald, Institute of Mathematics and Computer Science,Greifswald,Germany,17489","institution_ids":["https://openalex.org/I2799318839","https://openalex.org/I36522303"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050177044","display_name":"Oguzhan Ulucan","orcid":"https://orcid.org/0000-0003-2077-9691"},"institutions":[{"id":"https://openalex.org/I2799318839","display_name":"Universit\u00e4tsmedizin Greifswald","ror":"https://ror.org/025vngs54","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I2799318839"]},{"id":"https://openalex.org/I36522303","display_name":"Universit\u00e4t Greifswald","ror":"https://ror.org/00r1edq15","country_code":"DE","type":"education","lineage":["https://openalex.org/I36522303"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Oguzhan Ulucan","raw_affiliation_strings":["University of Greifswald, Institute of Mathematics and Computer Science,Greifswald,Germany,17489"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Greifswald, Institute of Mathematics and Computer Science,Greifswald,Germany,17489","institution_ids":["https://openalex.org/I2799318839","https://openalex.org/I36522303"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023822326","display_name":"Marc Ebner","orcid":"https://orcid.org/0000-0003-2725-2454"},"institutions":[{"id":"https://openalex.org/I2799318839","display_name":"Universit\u00e4tsmedizin Greifswald","ror":"https://ror.org/025vngs54","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I2799318839"]},{"id":"https://openalex.org/I36522303","display_name":"Universit\u00e4t Greifswald","ror":"https://ror.org/00r1edq15","country_code":"DE","type":"education","lineage":["https://openalex.org/I36522303"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marc Ebner","raw_affiliation_strings":["University of Greifswald, Institute of Mathematics and Computer Science,Greifswald,Germany,17489"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Greifswald, Institute of Mathematics and Computer Science,Greifswald,Germany,17489","institution_ids":["https://openalex.org/I2799318839","https://openalex.org/I36522303"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.66208115,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9125999808311462,"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":0.9125999808311462,"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":0.02800000086426735,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.00430000014603138,"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/image","display_name":"Image (mathematics)","score":0.5593000054359436},{"id":"https://openalex.org/keywords/color-constancy","display_name":"Color constancy","score":0.5428000092506409},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.46299999952316284},{"id":"https://openalex.org/keywords/image-gradient","display_name":"Image gradient","score":0.46149998903274536},{"id":"https://openalex.org/keywords/feature-detection","display_name":"Feature detection (computer vision)","score":0.44369998574256897},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4221999943256378},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4104999899864197},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.40119999647140503},{"id":"https://openalex.org/keywords/image-enhancement","display_name":"Image enhancement","score":0.39820000529289246},{"id":"https://openalex.org/keywords/reflectivity","display_name":"Reflectivity","score":0.3815000057220459}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7045999765396118},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6725999712944031},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5593000054359436},{"id":"https://openalex.org/C187888035","wikidata":"https://www.wikidata.org/wiki/Q2563885","display_name":"Color constancy","level":3,"score":0.5428000092506409},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.516700029373169},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.46299999952316284},{"id":"https://openalex.org/C182037307","wikidata":"https://www.wikidata.org/wiki/Q17039097","display_name":"Image gradient","level":5,"score":0.46149998903274536},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.44369998574256897},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4221999943256378},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4104999899864197},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.40119999647140503},{"id":"https://openalex.org/C3017601658","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image enhancement","level":3,"score":0.39820000529289246},{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.3815000057220459},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3774000108242035},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.3723999857902527},{"id":"https://openalex.org/C125045340","wikidata":"https://www.wikidata.org/wiki/Q6002224","display_name":"Image formation","level":3,"score":0.3652999997138977},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.3646000027656555},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.35040000081062317},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.34610000252723694},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3425000011920929},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.33399999141693115},{"id":"https://openalex.org/C2776674983","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image editing","level":3,"score":0.32600000500679016},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3222000002861023},{"id":"https://openalex.org/C142616399","wikidata":"https://www.wikidata.org/wiki/Q5148604","display_name":"Color image","level":4,"score":0.30970001220703125},{"id":"https://openalex.org/C36365805","wikidata":"https://www.wikidata.org/wiki/Q194411","display_name":"Illuminance","level":2,"score":0.29829999804496765},{"id":"https://openalex.org/C35772409","wikidata":"https://www.wikidata.org/wiki/Q1323086","display_name":"Image noise","level":3,"score":0.29260000586509705},{"id":"https://openalex.org/C180462255","wikidata":"https://www.wikidata.org/wiki/Q3559736","display_name":"Standard test image","level":4,"score":0.2825999855995178},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.2702000141143799},{"id":"https://openalex.org/C2778328480","wikidata":"https://www.wikidata.org/wiki/Q1639904","display_name":"Hybrid image","level":3,"score":0.2655999958515167},{"id":"https://openalex.org/C170130773","wikidata":"https://www.wikidata.org/wiki/Q216378","display_name":"Usability","level":2,"score":0.26109999418258667},{"id":"https://openalex.org/C120515352","wikidata":"https://www.wikidata.org/wiki/Q2564580","display_name":"Image plane","level":3,"score":0.2581000030040741},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.25529998540878296}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vcip67698.2025.11396892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip67698.2025.11396892","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.40657931566238403,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1580436348","https://openalex.org/W1938929646","https://openalex.org/W1987444808","https://openalex.org/W1994938019","https://openalex.org/W2052090926","https://openalex.org/W2054814429","https://openalex.org/W2087257250","https://openalex.org/W2090938122","https://openalex.org/W2102166818","https://openalex.org/W2113404166","https://openalex.org/W2116899452","https://openalex.org/W2118246710","https://openalex.org/W2125188192","https://openalex.org/W2133665775","https://openalex.org/W2164847484","https://openalex.org/W2288581841","https://openalex.org/W2405492408","https://openalex.org/W2412926690","https://openalex.org/W2468596194","https://openalex.org/W2566376500","https://openalex.org/W2948354154","https://openalex.org/W2981718299","https://openalex.org/W2986422266","https://openalex.org/W2998723654","https://openalex.org/W3015044426","https://openalex.org/W3022336857","https://openalex.org/W3034347506","https://openalex.org/W3034539499","https://openalex.org/W3035229960","https://openalex.org/W3035731588","https://openalex.org/W3083040138","https://openalex.org/W3120540810","https://openalex.org/W3121661546","https://openalex.org/W3125869362","https://openalex.org/W3171125843","https://openalex.org/W3174792937","https://openalex.org/W3209369922","https://openalex.org/W4200634150","https://openalex.org/W4214695428","https://openalex.org/W4250009291","https://openalex.org/W4290713858","https://openalex.org/W4306957749","https://openalex.org/W4312249431","https://openalex.org/W4313059954","https://openalex.org/W4386066362","https://openalex.org/W4386075858","https://openalex.org/W4387807122","https://openalex.org/W4389271971","https://openalex.org/W4390871817","https://openalex.org/W4390872514","https://openalex.org/W4394597326","https://openalex.org/W4403499874","https://openalex.org/W4404722383","https://openalex.org/W4406959532","https://openalex.org/W4417053443"],"related_works":[],"abstract_inverted_index":{"Low-light":[0],"image":[1,9,49,55,59,79,121,149,157],"enhancement":[2,158],"is":[3,45],"a":[4,103],"widely":[5],"studied":[6],"field":[7],"of":[8,102,119,129],"processing.":[10],"Over":[11],"the":[12,97,109,117,125,130],"past":[13],"decades,":[14],"numerous":[15],"successful":[16],"algorithms":[17],"have":[18],"been":[19],"proposed":[20,76],"to":[21,35,46,52,94,108,164],"address":[22],"its":[23,61,114],"challenges,":[24],"such":[25,64],"as":[26,65],"low":[27],"contrast,":[28],"color":[29],"fading,":[30],"and":[31,67,91,99,127,159],"noise.":[32],"One":[33],"way":[34],"enhance":[36],"dim":[37],"scenes":[38],"with":[39],"vivid":[40],"colors":[41],"while":[42],"suppressing":[43],"noise":[44],"apply":[47],"intrinsic":[48,78,148],"decomposition":[50,56,80],"prior":[51],"enhancement.":[53,122],"Intrinsic":[54],"separates":[57],"an":[58],"into":[60],"fundamental":[62],"components,":[63],"reflectance":[66,98],"shading.":[68],"In":[69],"this":[70,170],"study,":[71],"we":[72,112,132],"extent":[73],"our":[74,143],"recently":[75],"learning-free":[77],"method":[81],"based":[82],"on":[83,136],"Retinex":[84],"theory.":[85],"This":[86],"approach":[87],"utilizes":[88],"scale-space":[89],"computations":[90],"super-pixel":[92],"segmentation":[93],"effectively":[95],"estimate":[96],"shading":[100],"components":[101],"scene.":[104],"With":[105],"slight":[106],"modifications":[107],"original":[110],"method,":[111,131,144],"demonstrate":[113],"usability":[115],"in":[116],"context":[118],"low-light":[120,156],"To":[123],"validate":[124],"effectiveness":[126],"generalizability":[128],"conduct":[133],"comprehensive":[134],"experiments":[135],"five":[137],"benchmarks.":[138],"Our":[139],"results":[140,154],"show":[141],"that":[142],"originally":[145],"designed":[146],"for":[147,155,169],"decomposition,":[150],"can":[151],"produce":[152],"effective":[153],"achieve":[160],"competitive":[161],"performance":[162],"compared":[163],"learning-based":[165],"methods":[166],"specifically":[167],"developed":[168],"task.":[171]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-02-25T00:00:00"}
