{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:37:29Z","timestamp":1760233049500,"version":"build-2065373602"},"reference-count":68,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2022,12,17]],"date-time":"2022-12-17T00:00:00Z","timestamp":1671235200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation (NSF)","doi-asserted-by":"publisher","award":["CCF-2046293","FA9550-21-1-0330"],"award-info":[{"award-number":["CCF-2046293","FA9550-21-1-0330"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Air Force Office of Scientific Research (AFOSR)","award":["CCF-2046293","FA9550-21-1-0330"],"award-info":[{"award-number":["CCF-2046293","FA9550-21-1-0330"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, we present a framework to learn illumination patterns to improve the quality of signal recovery for coded diffraction imaging. We use an alternating minimization-based phase retrieval method with a fixed number of iterations as the iterative method. We represent the iterative phase retrieval method as an unrolled network with a fixed number of layers where each layer of the network corresponds to a single step of iteration, and we minimize the recovery error by optimizing over the illumination patterns. Since the number of iterations\/layers is fixed, the recovery has a fixed computational cost. Extensive experimental results on a variety of datasets demonstrate that our proposed method significantly improves the quality of image reconstruction at a fixed computational cost with illumination patterns learned only using a small number of training images.<\/jats:p>","DOI":"10.3390\/s22249964","type":"journal-article","created":{"date-parts":[[2022,12,19]],"date-time":"2022-12-19T09:31:01Z","timestamp":1671442261000},"page":"9964","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Learning to Sense for Coded Diffraction Imaging"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4191-301X","authenticated-orcid":false,"given":"Rakib","family":"Hyder","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of California, Riverside, CA 92521, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1663-9493","authenticated-orcid":false,"given":"Zikui","family":"Cai","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of California, Riverside, CA 92521, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5993-3903","authenticated-orcid":false,"given":"M. Salman","family":"Asif","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of California, Riverside, CA 92521, USA"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1364\/OL.3.000027","article-title":"Reconstruction of an object from the modulus of its Fourier transform","volume":"3","author":"Fienup","year":"1978","journal-title":"Opt. Lett."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1241","DOI":"10.1002\/cpa.21432","article-title":"Phaselift: Exact and stable signal recovery from magnitude measurements via convex programming","volume":"66","author":"Candes","year":"2013","journal-title":"Comm. Pure Appl. 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