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Earlier methods rely on hand-crafted filters or priors and still exhibit disturbing visual artifacts in hard cases such as moir\u00e9 or thin edges. We introduce a new data-driven approach for these challenges: we train a deep neural network on a large corpus of images instead of using hand-tuned filters. While deep learning has shown great success, its naive application using existing training datasets does not give satisfactory results for our problem because these datasets lack hard cases. To create a better training set, we present metrics to identify difficult patches and techniques for mining community photographs for such patches. Our experiments show that this network and training procedure outperform state-of-the-art both on noisy and noise-free data. Furthermore, our algorithm is an order of magnitude faster than the previous best performing techniques.<\/jats:p>","DOI":"10.1145\/2980179.2982399","type":"journal-article","created":{"date-parts":[[2016,11,11]],"date-time":"2016-11-11T17:02:54Z","timestamp":1478883774000},"page":"1-12","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":410,"title":["Deep joint demosaicking and denoising"],"prefix":"10.1145","volume":"35","author":[{"given":"Micha\u00ebl","family":"Gharbi","sequence":"first","affiliation":[{"name":"MIT CSAIL"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gaurav","family":"Chaurasia","sequence":"additional","affiliation":[{"name":"MIT CSAIL"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sylvain","family":"Paris","sequence":"additional","affiliation":[{"name":"Adobe"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fr\u00e9do","family":"Durand","sequence":"additional","affiliation":[{"name":"MIT CSAIL"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2016,12,5]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Image Processing (ICIP), 2015 IEEE International Conference on, 4778--4782","author":"Akiyama H.","unstructured":"Akiyama , H. , Tanaka , M. , and Okutomi , M . 2015. 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