{"id":154996,"date":"2020-02-20T11:35:32","date_gmt":"2006-06-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/noise-estimation-from-a-single-image\/"},"modified":"2020-11-03T18:27:22","modified_gmt":"2020-11-04T02:27:22","slug":"noise-estimation-from-a-single-image","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/noise-estimation-from-a-single-image\/","title":{"rendered":"Noise Estimation from a Single Image"},"content":{"rendered":"<div class=\"asset-content\">\n<p>In order to work well, many computer vision algorithms require that their parameters be adjusted according to the image noise level, making it an important quantity to estimate. We show how to estimate an upper bound on the noise level from a single image based on a piecewise smooth image prior model and measured CCD camera response functions. We also learn the space of noise level functions\u2013how noise level changes with respect to brightness\u2013and use Bayesian MAP inference to infer the noise level function from a single image. We illustrate the utility of this noise estimation for two algorithms: edge detection and featurepreserving smoothing through bilateral filtering. For a variety of different noise levels, we obtain good results for both these algorithms with no user-specified inputs.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In order to work well, many computer vision algorithms require that their parameters be adjusted according to the image noise level, making it an important quantity to estimate. We show how to estimate an upper bound on the noise level from a single image based on a piecewise smooth image prior model and measured CCD [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":[{"type":"user_nicename","value":"sbkang"},{"type":"user_nicename","value":"szeliski"}],"msr_publishername":"IEEE Computer Society","msr_publisher_other":"","msr_booktitle":"IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'2006)","msr_chapter":"","msr_edition":"IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'2006)","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"901-908","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"2","msr_copyright":"Copyright \u00a9 2007 IEEE.   Reprinted from IEEE Computer Society.\r\n\r\nThis material is posted here with permission of the IEEE.  Internal or personal use of this material is permitted.  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