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To record images without optical aberrations, i.e., deviations from Gauss' linear model of optics, typical lens systems introduce increasingly complex stacks of optical elements which are responsible for the height of existing commodity cameras. In this work, we investigate\n            <jats:italic toggle=\"yes\">flat nanophotonic computational cameras<\/jats:italic>\n            as an alternative that employs an array of skewed lenslets and a learned reconstruction approach. The optical array is embedded on a metasurface that, at 700 nm height, is flat and sits on the sensor cover glass at 2.5 mm focal distance from the sensor. To tackle the highly chromatic response of a metasurface and design the array over the entire sensor, we propose a differentiable optimization method that continuously samples over the visible spectrum and factorizes the optical modulation for different incident fields into individual lenses. We reconstruct a megapixel image from our flat imager with a\n            <jats:italic toggle=\"yes\">learned probabilistic reconstruction<\/jats:italic>\n            method that employs a generative diffusion model to sample an implicit prior. To tackle\n            <jats:italic toggle=\"yes\">scene-dependent aberrations in broadband<\/jats:italic>\n            , we propose a method for acquiring paired captured training data in varying illumination conditions. We assess the proposed flat camera design in simulation and with an experimental prototype, validating that the method is capable of recovering images from diverse scenes in broadband with a single nanophotonic layer.\n          <\/jats:p>","DOI":"10.1145\/3618398","type":"journal-article","created":{"date-parts":[[2023,12,5]],"date-time":"2023-12-05T10:20:48Z","timestamp":1701771648000},"page":"1-18","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":27,"title":["Thin On-Sensor Nanophotonic Array Cameras"],"prefix":"10.1145","volume":"42","author":[{"given":"Praneeth","family":"Chakravarthula","sequence":"first","affiliation":[{"name":"Princeton University, USA"}]},{"given":"Jipeng","family":"Sun","sequence":"additional","affiliation":[{"name":"Princeton University, USA"}]},{"given":"Xiao","family":"Li","sequence":"additional","affiliation":[{"name":"Princeton University, USA"}]},{"given":"Chenyang","family":"Lei","sequence":"additional","affiliation":[{"name":"Princeton University, USA"}]},{"given":"Gene","family":"Chou","sequence":"additional","affiliation":[{"name":"Princeton University, USA"}]},{"given":"Mario","family":"Bijelic","sequence":"additional","affiliation":[{"name":"Princeton University, USA"}]},{"given":"Johannes","family":"Froesch","sequence":"additional","affiliation":[{"name":"University of Washington, USA"}]},{"given":"Arka","family":"Majumdar","sequence":"additional","affiliation":[{"name":"University of Washington, USA"}]},{"given":"Felix","family":"Heide","sequence":"additional","affiliation":[{"name":"Princeton University, USA"}]}],"member":"320","published-online":{"date-parts":[[2023,12,5]]},"reference":[{"key":"e_1_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1021\/nl302516v"},{"key":"e_1_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.aaa2494"},{"key":"e_1_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1364\/OPTICA.5.000001"},{"key":"e_1_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1038\/nnano.2015.186"},{"key":"e_1_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1364\/OPTICA.3.000628"},{"key":"e_1_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1364\/OPTICA.4.000625"},{"key":"e_1_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1021\/acsphotonics.8b00362"},{"key":"e_1_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCI.2016.2593662"},{"key":"e_1_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCI.2016.2593662"},{"key":"e_1_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00570"},{"key":"e_1_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00265"},{"key":"e_1_2_2_12_1","volume-title":"Introduction to inverse problems in imaging","author":"Bertero Mario","unstructured":"Mario Bertero, Patrizia Boccacci, and Christine De Mol. 2021. 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A Machine Learning Approach for Non-blind Image Deconvolution. In Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 1067--1074."},{"key":"e_1_2_2_68_1","volume-title":"Multicolour localization microscopy by point-spread-function engineering. Nature photonics 10","author":"Shechtman Yoav","year":"2016","unstructured":"Yoav Shechtman, Lucien E Weiss, Adam S. Backer, Maurice Y. Lee, and W E Moerner. 2016. Multicolour localization microscopy by point-spread-function engineering. Nature photonics 10 (2016), 590--594."},{"key":"e_1_2_2_69_1","doi-asserted-by":"publisher","DOI":"10.1145\/3528223.3530185"},{"key":"e_1_2_2_70_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41377-018-0078-x"},{"key":"e_1_2_2_71_1","doi-asserted-by":"publisher","DOI":"10.1145\/3197517.3201333"},{"key":"e_1_2_2_72_1","volume-title":"International Conference on Machine Learning. 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