{"id":"https://openalex.org/W4310337940","doi":"https://doi.org/10.1109/avss56176.2022.9959170","title":"SAR Image Denoising in High Dynamic Range with Speckle and Thermal Noise Refinement Modeling","display_name":"SAR Image Denoising in High Dynamic Range with Speckle and Thermal Noise Refinement Modeling","publication_year":2022,"publication_date":"2022-11-24","ids":{"openalex":"https://openalex.org/W4310337940","doi":"https://doi.org/10.1109/avss56176.2022.9959170"},"language":"en","primary_location":{"id":"doi:10.1109/avss56176.2022.9959170","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss56176.2022.9959170","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 18th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","raw_type":"proceedings-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/A5101657505","display_name":"Ji-Hoon Han","orcid":"https://orcid.org/0009-0003-4167-7253"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Ji-Hoon Han","raw_affiliation_strings":["Korea University,Seoul,Korea","Korea University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Korea University,Seoul,Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"Korea University, Seoul, Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109442512","display_name":"Woo-Jeoung Nam","orcid":null},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Woo-Jeoung Nam","raw_affiliation_strings":["Korea University,Seoul,Korea","Korea University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Korea University,Seoul,Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"Korea University, Seoul, Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011014617","display_name":"Seong\u2010Whan Lee","orcid":"https://orcid.org/0000-0002-6249-4996"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seong-Whan Lee","raw_affiliation_strings":["Korea University,Seoul,Korea","Korea University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Korea University,Seoul,Korea","institution_ids":["https://openalex.org/I197347611"]},{"raw_affiliation_string":"Korea University, Seoul, Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101657505"],"corresponding_institution_ids":["https://openalex.org/I197347611"],"apc_list":null,"apc_paid":null,"fwci":0.2012,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.48818487,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"3","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","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/T10688","display_name":"Image and Signal Denoising Methods","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/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9958999752998352,"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9955999851226807,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/speckle-noise","display_name":"Speckle noise","score":0.8095734119415283},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7235693335533142},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6634979844093323},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6280784010887146},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6209107637405396},{"id":"https://openalex.org/keywords/speckle-pattern","display_name":"Speckle pattern","score":0.5852416753768921},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.5577732920646667},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.47497838735580444},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4435465335845947},{"id":"https://openalex.org/keywords/high-dynamic-range","display_name":"High dynamic range","score":0.4316731095314026},{"id":"https://openalex.org/keywords/dynamic-range","display_name":"Dynamic range","score":0.38476133346557617},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.330011785030365},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24053895473480225}],"concepts":[{"id":"https://openalex.org/C180940675","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle noise","level":3,"score":0.8095734119415283},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7235693335533142},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6634979844093323},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6280784010887146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6209107637405396},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.5852416753768921},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.5577732920646667},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47497838735580444},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4435465335845947},{"id":"https://openalex.org/C2780056265","wikidata":"https://www.wikidata.org/wiki/Q106239881","display_name":"High dynamic range","level":3,"score":0.4316731095314026},{"id":"https://openalex.org/C87133666","wikidata":"https://www.wikidata.org/wiki/Q1161699","display_name":"Dynamic range","level":2,"score":0.38476133346557617},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.330011785030365},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24053895473480225}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/avss56176.2022.9959170","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss56176.2022.9959170","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 18th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.5199999809265137,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321373","display_name":"Korea University","ror":"https://ror.org/047dqcg40"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1600455797","https://openalex.org/W1996160600","https://openalex.org/W1998266997","https://openalex.org/W2004376198","https://openalex.org/W2064076387","https://openalex.org/W2074319623","https://openalex.org/W2079299474","https://openalex.org/W2104763670","https://openalex.org/W2117294245","https://openalex.org/W2133954466","https://openalex.org/W2144851790","https://openalex.org/W2162457349","https://openalex.org/W2508457857","https://openalex.org/W2515866431","https://openalex.org/W2562637781","https://openalex.org/W2604403460","https://openalex.org/W2621042270","https://openalex.org/W2757678917","https://openalex.org/W2954537798","https://openalex.org/W2963583038","https://openalex.org/W3000775737","https://openalex.org/W3037578234","https://openalex.org/W3105577662","https://openalex.org/W3136138438"],"related_works":["https://openalex.org/W2065648684","https://openalex.org/W2009383287","https://openalex.org/W2042914788","https://openalex.org/W2182190754","https://openalex.org/W4321264664","https://openalex.org/W2121688719","https://openalex.org/W2727313114","https://openalex.org/W2016481886","https://openalex.org/W2884377208","https://openalex.org/W2055824452"],"abstract_inverted_index":{"Synthetic":[0],"Aperture":[1],"Radar":[2],"(SAR)":[3],"images":[4,11,41],"inevitably":[5],"contain":[6],"speckle":[7,79],"noise.":[8,126],"Despeckling":[9],"SAR":[10,40],"are":[12,42],"typically":[13],"represented":[14],"as":[15],"linear":[16,29,39],"forms":[17],"due":[18,62],"to":[19,34,63,98,123,141],"the":[20,38,45,64,84,96,101,105,120,142],"consistency":[21],"of":[22,50,104],"denoising":[23,74],"network":[24,97],"training/inference":[25],"settings":[26],"on":[27],"a":[28,73],"scale.":[30],"However,":[31],"this":[32],"leads":[33],"controversial":[35],"problems":[36],"when":[37],"seen":[43],"with":[44],"naked":[46],"eye:":[47],"i)":[48],"restriction":[49],"representation":[51],"for":[52,59],"dark":[53],"areas":[54,61],"and":[55,80,137],"ii)":[56],"excessive":[57],"expression":[58],"bright":[60],"high-intensity":[65],"range.":[66],"To":[67],"overcome":[68],"these":[69],"problems,":[70],"we":[71],"propose":[72],"framework":[75],"that":[76,130],"simultaneously":[77],"eliminates":[78],"thermal":[81,125],"noise":[82,90,93],"in":[83,100,135],"decibel":[85],"(dB)":[86],"domain":[87,103],"through":[88],"novel":[89],"modeling.":[91],"Our":[92,117],"modeling":[94,118],"allows":[95],"learn":[99],"dB":[102],"desired":[106],"dynamic":[107],"range,":[108],"enabling":[109],"stable":[110],"end-to-end":[111],"learning":[112],"without":[113],"separate":[114],"spatial":[115],"transformations.":[116],"is":[119,133],"first":[121],"attempt":[122],"consider":[124],"Experimental":[127],"results":[128],"show":[129],"our":[131],"method":[132],"superior":[134],"quantitative":[136],"visual":[138],"performance":[139],"compared":[140],"existing":[143],"methods.":[144]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
