{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T13:01:55Z","timestamp":1789218115615,"version":"build-2803163510"},"reference-count":29,"publisher":"Optica Publishing Group","issue":"26","license":[{"start":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T00:00:00Z","timestamp":1766534400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/doi.org\/10.1364\/OA_License_v2#VOR-OA"},{"start":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T00:00:00Z","timestamp":1766534400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/opg.optica.org\/policies\/opg-tdm-policy.json"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["92364108"],"award-info":[{"award-number":["92364108"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Project of Jiangsu Underground Space Intelligent Touch Operation and Maintenance Engineering Technology Research and Development Center in 2025","award":["jsdxkizh-2024-17"],"award-info":[{"award-number":["jsdxkizh-2024-17"]}]},{"name":"Natural Science Foundation of the Jiangsu Higher Education Institutions of China","award":["24KJD510005"],"award-info":[{"award-number":["24KJD510005"]}]}],"content-domain":{"domain":["opg.optica.org"],"crossmark-restriction":false},"short-container-title":["Opt. Express"],"published-print":{"date-parts":[[2025,12,29]]},"abstract":"<jats:p>\n                    Snapshot polarimetric imaging systems using division of focal plane (DoFP) sensors efficiently capture scene polarization information, but the spatial multiplexing of micro-polarizer arrays leads to a loss of spatial resolution. Current learning-based polarization image reconstruction methods, although achieving excellent performance by directly learning the mapping from low resolution to high resolution, often neglect the inherent physical mechanisms of polarization image reconstruction. This paper proposes a deep unfolding network for polarization image reconstruction called DUPIR, which jointly reconstructs full-resolution intensity images for the four linear polarization orientations\n                    <jats:italic toggle=\"yes\">I<\/jats:italic>\n                    <jats:sub>0<\/jats:sub>\n                    ,\n                    <jats:italic toggle=\"yes\">I<\/jats:italic>\n                    <jats:sub>45<\/jats:sub>\n                    ,\n                    <jats:italic toggle=\"yes\">I<\/jats:italic>\n                    <jats:sub>90<\/jats:sub>\n                    , and\n                    <jats:italic toggle=\"yes\">I<\/jats:italic>\n                    <jats:sub>135<\/jats:sub>\n                    , along with their corresponding polarization parameters Stokes S\n                    <jats:sub>0<\/jats:sub>\n                    , the degree of linear polarization DoLP, and the angle of polarization AoP, in an end-to-end manner. By integrating physical model priors into a trainable architecture, DUPIR bridges the gap between model-based and learning-based methods. To mitigate the lack of high-quality training data, a polarization dataset comprising 184 sample pairs from various object categories was established. Extensive experiments on both public and our collected datasets demonstrate that DUPIR achieves state-of-the-art reconstruction accuracy while maintaining real-time inference capability.\n                  <\/jats:p>","DOI":"10.1364\/oe.581615","type":"journal-article","created":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T08:00:07Z","timestamp":1765440007000},"page":"55139","update-policy":"https:\/\/doi.org\/10.1364\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["End-to-end deep unfolding network for DoFP polarization image reconstruction"],"prefix":"10.1364","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-5770-5923","authenticated-orcid":true,"given":"Xin","family":"Liu","sequence":"first","affiliation":[{"name":"Southeast University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiqiu","family":"Yan","sequence":"additional","affiliation":[{"name":"Southeast University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenyuan","family":"Huang","sequence":"additional","affiliation":[{"name":"Southeast University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pan","family":"Wang","sequence":"additional","affiliation":[{"name":"Southeast University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siju","family":"Peng","sequence":"additional","affiliation":[{"name":"Southeast University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanxing","family":"Zhao","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Wang","sequence":"additional","affiliation":[{"name":"Nanjing University of Industry Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6161-1911","authenticated-orcid":true,"given":"Qilong","family":"Wang","sequence":"additional","affiliation":[{"name":"Southeast University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"285","published-online":{"date-parts":[[2025,12,24]]},"reference":[{"key":"oe-33-26-55139-R1","doi-asserted-by":"publisher","first-page":"1692","DOI":"10.1109\/JSEN.2010.2095003","type":"journal-article","volume":"11","author":"Sarkar","year":"2011","journal-title":"IEEE Sens. 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