{"id":"https://openalex.org/W4415491315","doi":"https://doi.org/10.1142/s0219691325500365","title":"A deep-learning single-shot phase retrieval approach with <i>ABCD</i> matrices","display_name":"A deep-learning single-shot phase retrieval approach with <i>ABCD</i> matrices","publication_year":2025,"publication_date":"2025-10-24","ids":{"openalex":"https://openalex.org/W4415491315","doi":"https://doi.org/10.1142/s0219691325500365"},"language":"en","primary_location":{"id":"doi:10.1142/s0219691325500365","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219691325500365","pdf_url":null,"source":{"id":"https://openalex.org/S56986848","display_name":"International Journal of Wavelets Multiresolution and Information Processing","issn_l":"0219-6913","issn":["0219-6913","1793-690X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Wavelets, Multiresolution and Information Processing","raw_type":"journal-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":null,"display_name":"Shufan Lin","orcid":"https://orcid.org/0009-0009-7588-4721"},"institutions":[{"id":"https://openalex.org/I181903023","display_name":"Xi'an Shiyou University","ror":"https://ror.org/040c7js64","country_code":"CN","type":"education","lineage":["https://openalex.org/I181903023"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shufan Lin","raw_affiliation_strings":["School of Science, Xi\u2019an Shiyou University, Shaanxi 710065, P. R. China"],"raw_orcid":"https://orcid.org/0009-0009-7588-4721","affiliations":[{"raw_affiliation_string":"School of Science, Xi\u2019an Shiyou University, Shaanxi 710065, P. R. China","institution_ids":["https://openalex.org/I181903023"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102207652","display_name":"Haiwei Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I181903023","display_name":"Xi'an Shiyou University","ror":"https://ror.org/040c7js64","country_code":"CN","type":"education","lineage":["https://openalex.org/I181903023"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiwei Fu","raw_affiliation_strings":["School of Science, Xi\u2019an Shiyou University, Shaanxi 710065, P. R. China"],"raw_orcid":"https://orcid.org/0009-0008-7224-8052","affiliations":[{"raw_affiliation_string":"School of Science, Xi\u2019an Shiyou University, Shaanxi 710065, P. R. China","institution_ids":["https://openalex.org/I181903023"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I181903023"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.35871002,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"24","issue":"01","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11183","display_name":"Advanced X-ray Imaging Techniques","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11183","display_name":"Advanced X-ray Imaging Techniques","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11949","display_name":"Nuclear Physics and Applications","score":0.9642000198364258,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11733","display_name":"X-ray Spectroscopy and Fluorescence Analysis","score":0.9129999876022339,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/phase-retrieval","display_name":"Phase retrieval","score":0.8504999876022339},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6866000294685364},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.6173999905586243},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5011000037193298},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4214000105857849},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.39579999446868896},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3799999952316284},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.3671000003814697},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.36570000648498535}],"concepts":[{"id":"https://openalex.org/C81793267","wikidata":"https://www.wikidata.org/wiki/Q7180962","display_name":"Phase retrieval","level":3,"score":0.8504999876022339},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6866000294685364},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6682999730110168},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.6173999905586243},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.592199981212616},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5011000037193298},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4415999948978424},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4214000105857849},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.39579999446868896},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3799999952316284},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.3671000003814697},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.36570000648498535},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36410000920295715},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.36329999566078186},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.33070001006126404},{"id":"https://openalex.org/C70958404","wikidata":"https://www.wikidata.org/wiki/Q7512728","display_name":"Signal reconstruction","level":4,"score":0.3273000121116638},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.3212999999523163},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.31709998846054077},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31540000438690186},{"id":"https://openalex.org/C166386157","wikidata":"https://www.wikidata.org/wiki/Q1477735","display_name":"Short-time Fourier transform","level":4,"score":0.3118000030517578},{"id":"https://openalex.org/C57733114","wikidata":"https://www.wikidata.org/wiki/Q1006032","display_name":"Discrete Fourier transform (general)","level":5,"score":0.3034999966621399},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.30230000615119934},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2955999970436096},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.29510000348091125},{"id":"https://openalex.org/C3019555358","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Fourier domain","level":3,"score":0.2944999933242798},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2935999929904938},{"id":"https://openalex.org/C2780427248","wikidata":"https://www.wikidata.org/wiki/Q17014996","display_name":"Fundamental matrix (linear differential equation)","level":2,"score":0.2919999957084656},{"id":"https://openalex.org/C93509452","wikidata":"https://www.wikidata.org/wiki/Q7180943","display_name":"Phase correlation","level":5,"score":0.2824000120162964},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.2824000120162964},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.26019999384880066},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2583000063896179}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0219691325500365","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219691325500365","pdf_url":null,"source":{"id":"https://openalex.org/S56986848","display_name":"International Journal of Wavelets Multiresolution and Information Processing","issn_l":"0219-6913","issn":["0219-6913","1793-690X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Wavelets, Multiresolution and Information Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7110645028","display_name":null,"funder_award_id":"2019GY-176","funder_id":"https://openalex.org/F4320336350","funder_display_name":"Key Research and Development Projects of Shaanxi Province"}],"funders":[{"id":"https://openalex.org/F4320336350","display_name":"Key Research and Development Projects of Shaanxi Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1976272929","https://openalex.org/W2007593159","https://openalex.org/W2019013972","https://openalex.org/W2041078798","https://openalex.org/W2062313409","https://openalex.org/W2075233116","https://openalex.org/W2092968959","https://openalex.org/W2132984323","https://openalex.org/W2158721499","https://openalex.org/W2424581959","https://openalex.org/W2508457857","https://openalex.org/W2551898668","https://openalex.org/W2741137940","https://openalex.org/W2912697496","https://openalex.org/W2923054028","https://openalex.org/W3157840204","https://openalex.org/W3159174613","https://openalex.org/W4200300529","https://openalex.org/W4205245139","https://openalex.org/W4223516921","https://openalex.org/W4225616056","https://openalex.org/W4255272544","https://openalex.org/W4306796474","https://openalex.org/W4385454453","https://openalex.org/W4389619381","https://openalex.org/W4390475396","https://openalex.org/W4401961304","https://openalex.org/W4403028911","https://openalex.org/W4403749035"],"related_works":[],"abstract_inverted_index":{"The":[0],"phase":[1,26,48],"retrieval":[2,49],"problem":[3],"centers":[4],"on":[5,52,120],"reconstructing":[6],"a":[7,18,46,53,73,81,88,97],"signal":[8],"or":[9,107],"image":[10,84],"from":[11,96],"the":[12,22,102,117,121],"magnitude":[13],"of":[14,25],"its":[15,149],"Fourier":[16,32,62],"transform,":[17,57],"task":[19],"complicated":[20],"by":[21],"inherent":[23],"loss":[24],"information.":[27],"Single-shot":[28],"intensity":[29,99],"measurements":[30],"in":[31,112,145],"domain":[33],"are":[34],"typically":[35],"insufficient":[36],"for":[37,104],"accurate":[38],"recovery.":[39],"To":[40],"address":[41],"this":[42],"challenge,":[43],"we":[44],"introduce":[45],"novel":[47],"framework":[50,140],"based":[51],"generalized":[54],"ABCD":[55],"matrix":[56],"which":[58],"unifies":[59],"Fourier,":[60],"fractional":[61],"and":[63,123,151],"linear":[64],"canonical":[65],"transform":[66],"domains.":[67],"Our":[68],"approach":[69],"is":[70],"implemented":[71],"within":[72],"self-supervised,":[74],"end-to-end":[75],"deep":[76],"learning":[77],"architecture":[78],"that":[79,138],"integrates":[80],"local":[82],"implicit":[83],"function":[85],"(LIIF)":[86],"with":[87],"super-resolution":[89],"module.":[90],"This":[91],"design":[92],"enables":[93],"direct":[94],"reconstruction":[95,146],"single":[98],"measurement,":[100],"eliminating":[101],"need":[103],"multiple":[105],"acquisitions":[106],"iterative":[108],"refinement":[109],"commonly":[110],"required":[111],"classical":[113],"settings.":[114],"We":[115],"evaluate":[116],"proposed":[118],"method":[119],"DIV2K":[122],"Set12":[124],"benchmark":[125],"datasets":[126],"using":[127],"selected":[128],"parameter":[129],"configurations.":[130],"Extensive":[131],"experiments,":[132],"including":[133],"an":[134],"ablation":[135],"study,":[136],"demonstrate":[137],"our":[139],"consistently":[141],"outperforms":[142],"existing":[143],"algorithms":[144],"fidelity,":[147],"underscoring":[148],"robustness":[150],"practical":[152],"effectiveness.":[153]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-24T00:00:00"}