{"id":"https://openalex.org/W3194136660","doi":"https://doi.org/10.1109/icip42928.2021.9506575","title":"High-Frequency Preserving Image Downscaler","display_name":"High-Frequency Preserving Image Downscaler","publication_year":2021,"publication_date":"2021-08-23","ids":{"openalex":"https://openalex.org/W3194136660","doi":"https://doi.org/10.1109/icip42928.2021.9506575","mag":"3194136660"},"language":"en","primary_location":{"id":"doi:10.1109/icip42928.2021.9506575","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip42928.2021.9506575","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Image Processing (ICIP)","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/A5100447941","display_name":"Jaehwan Kim","orcid":"https://orcid.org/0000-0002-6152-2924"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaehwan Kim","raw_affiliation_strings":["Samsung Electronics,Samsung Research,Korea","Samsung Research, Samsung Electronics, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Electronics,Samsung Research,Korea","institution_ids":["https://openalex.org/I2250650973"]},{"raw_affiliation_string":"Samsung Research, Samsung Electronics, Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100848462","display_name":"Soo Min Kang","orcid":null},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Soo Min Kang","raw_affiliation_strings":["Samsung Electronics,Samsung Research,Korea","Samsung Research, Samsung Electronics, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Electronics,Samsung Research,Korea","institution_ids":["https://openalex.org/I2250650973"]},{"raw_affiliation_string":"Samsung Research, Samsung Electronics, Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101522014","display_name":"Kwang Pyo Choi","orcid":"https://orcid.org/0000-0003-1638-5446"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kwang Pyo Choi","raw_affiliation_strings":["Samsung Electronics,Samsung Research,Korea","Samsung Research, Samsung Electronics, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Electronics,Samsung Research,Korea","institution_ids":["https://openalex.org/I2250650973"]},{"raw_affiliation_string":"Samsung Research, Samsung Electronics, Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036459840","display_name":"Youngo Park","orcid":null},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Youngo Park","raw_affiliation_strings":["Samsung Electronics,Samsung Research,Korea","Samsung Research, Samsung Electronics, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Electronics,Samsung Research,Korea","institution_ids":["https://openalex.org/I2250650973"]},{"raw_affiliation_string":"Samsung Research, Samsung Electronics, Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089627967","display_name":"Chaeeun Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chaeeun Lee","raw_affiliation_strings":["Samsung Electronics,Samsung Research,Korea","Samsung Research, Samsung Electronics, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Electronics,Samsung Research,Korea","institution_ids":["https://openalex.org/I2250650973"]},{"raw_affiliation_string":"Samsung Research, Samsung Electronics, Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100668167","display_name":"Jong\u2010Seok Lee","orcid":"https://orcid.org/0000-0002-8038-1119"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jongseok Lee","raw_affiliation_strings":["Samsung Electronics,Samsung Research,Korea","Samsung Research, Samsung Electronics, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Samsung Electronics,Samsung Research,Korea","institution_ids":["https://openalex.org/I2250650973"]},{"raw_affiliation_string":"Samsung Research, Samsung Electronics, Korea","institution_ids":["https://openalex.org/I2250650973"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2250650973"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09782959,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"1984","last_page":"1988"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998999834060669,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9998999834060669,"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":0.9991999864578247,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9976000189781189,"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/autoencoder","display_name":"Autoencoder","score":0.8609268665313721},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7335540056228638},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7221037149429321},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6949087381362915},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6754601001739502},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5905795097351074},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5611516237258911},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.42632415890693665},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41954436898231506},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3429679274559021}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8609268665313721},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7335540056228638},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7221037149429321},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6949087381362915},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6754601001739502},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5905795097351074},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5611516237258911},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.42632415890693665},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41954436898231506},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3429679274559021},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip42928.2021.9506575","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip42928.2021.9506575","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1523113578","https://openalex.org/W1791560514","https://openalex.org/W1885185971","https://openalex.org/W1930824406","https://openalex.org/W1987278426","https://openalex.org/W1992605861","https://openalex.org/W2017522196","https://openalex.org/W2047215160","https://openalex.org/W2117539524","https://openalex.org/W2121927366","https://openalex.org/W2133665775","https://openalex.org/W2152818797","https://openalex.org/W2551276706","https://openalex.org/W2562637781","https://openalex.org/W2740404827","https://openalex.org/W2741137940","https://openalex.org/W2770079654","https://openalex.org/W2866634454","https://openalex.org/W2894234546","https://openalex.org/W2897552070","https://openalex.org/W2932253358","https://openalex.org/W2943960148","https://openalex.org/W2963372104","https://openalex.org/W3098668600","https://openalex.org/W4377561911","https://openalex.org/W6631190155","https://openalex.org/W6638194035","https://openalex.org/W6653418552","https://openalex.org/W6662276203","https://openalex.org/W6741655702","https://openalex.org/W6753074096","https://openalex.org/W6785366378"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4392946183","https://openalex.org/W3088732000"],"abstract_inverted_index":{"The":[0],"goal":[1],"of":[2,20,50,73,93,123],"downscaling":[3],"an":[4,63,79],"image":[5,54,65,76,85,105],"is":[6,81,87],"to":[7,11,41,47,107,131],"reduce":[8],"its":[9],"resolution":[10,53],"a":[12,100],"lower":[13],"resolution,":[14],"while":[15],"maintaining":[16],"the":[17,21,48,69,74,84,91,94,118,124],"visual":[18],"characteristics":[19],"original":[22,75],"image.":[23],"Recent":[24],"learning-based":[25],"algorithms":[26],"have":[27],"shown":[28],"great":[29],"improvement":[30],"over":[31],"conventional":[32],"methods":[33],"in":[34,56],"preserving":[35],"high-frequency":[36],"information.":[37],"However,":[38],"they":[39],"continue":[40],"suffer":[42],"from":[43],"various":[44,128],"artifacts":[45],"due":[46],"lack":[49],"true":[51],"high-low":[52],"pairs":[55],"their":[57],"training":[58],"datasets.":[59],"In":[60],"this":[61],"paper,":[62],"unsupervised":[64],"downscaler":[66,86,106],"that":[67,103],"preserves":[68],"high":[70],"frequency":[71],"content":[72],"based":[77],"on":[78,113],"autoencoder":[80],"presented.":[82],"Specifically,":[83],"obtained":[88],"by":[89],"extracting":[90],"decoder":[92],"developed":[95],"autoencoder.":[96],"Furthermore,":[97],"we":[98],"propose":[99],"preprocessing":[101],"step":[102],"enables":[104],"any":[108],"arbitrary":[109],"scales.":[110],"Experimental":[111],"results":[112],"five":[114],"benchmark":[115],"datasets":[116],"reveal":[117],"qualitative":[119],"and":[120],"quantitative":[121],"superiority":[122],"proposed":[125],"method":[126],"at":[127],"scales":[129],"compared":[130],"other":[132],"methods.":[133]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
