{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/automatic-estimation-of-modulation-transfer","title":"Automatic Estimation of Modulation Transfer Functions","arxiv_id":"1805.01872","date":"2018-05-04","proceeding":null,"authors":["Matthias Bauer","Valentin Volchkov","Michael Hirsch","Bernhard Schölkopf"],"abstract":"The modulation transfer function (MTF) is widely used to characterise the\nperformance of optical systems. Measuring it is costly and it is thus rarely\navailable for a given lens specimen. Instead, MTFs based on simulations or, at\nbest, MTFs measured on other specimens of the same lens are used. Fortunately,\nimages recorded through an optical system contain ample information about its\nMTF, only that it is confounded with the statistics of the images. This work\npresents a method to estimate the MTF of camera lens systems directly from\nphotographs, without the need for expensive equipment. We use a custom grid\ndisplay to accurately measure the point response of lenses to acquire ground\ntruth training data. We then use the same lenses to record natural images and\nemploy a data-driven supervised learning approach using a convolutional neural\nnetwork to estimate the MTF on small image patches, aggregating the information\ninto MTF charts over the entire field of view. It generalises to unseen lenses\nand can be applied for single photographs, with the performance improving if\nmultiple photographs are available.","url_abs":"http://arxiv.org/abs/1805.01872v1","url_pdf":"http://arxiv.org/pdf/1805.01872v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"automatic-estimation-of-modulation-transfer","repo_url":"https://github.com/ajpfahnl/MTF-and-Linearity","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1805.01872","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}