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Our approach can handle large sets of images, acquired from a nearly planar or infinitely distant scene at different resolutions in object domain and under variable local or global illumination conditions. It allows for efficient user guidance as its progressive nature provides a valid and consistent reconstruction at any moment during the online refinement\u00a0process.<\/jats:p><jats:p>Our approach avoids global optimization techniques, as commonly used in the field of image refinement, and progressively incorporates new imagery into a dynamically extendable and memory\u2010efficient Laplacian pyramid. Our image registration process includes a coarse homography and a local refinement stage using optical flow. Photometric consistency is achieved by retaining the photometric intensities given in a reference image, while it is being refined. Globally blurred imagery and local geometric inconsistencies due to, e.g. motion are detected and removed prior to image\u00a0fusion.<\/jats:p><jats:p>We demonstrate the quality and robustness of our approach using several image and video sequences, including handheld acquisition with mobile phones and zooming sequences with consumer\u00a0cameras.<\/jats:p>","DOI":"10.1111\/cgf.13808","type":"journal-article","created":{"date-parts":[[2019,9,5]],"date-time":"2019-09-05T06:42:57Z","timestamp":1567665777000},"page":"360-374","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Progressive Refinement Imaging"],"prefix":"10.1111","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6815-807X","authenticated-orcid":false,"given":"M.","family":"Kluge","sequence":"first","affiliation":[{"name":"Computer Graphics Group University of Siegen Germany"}]},{"given":"T.","family":"Weyrich","sequence":"additional","affiliation":[{"name":"Department of Computer Science University College London UK"}]},{"given":"A.","family":"Kolb","sequence":"additional","affiliation":[{"name":"Computer Graphics Group University of Siegen Germany"}]}],"member":"311","published-online":{"date-parts":[[2019,9,4]]},"reference":[{"key":"e_1_2_8_2_1","first-page":"33","article-title":"Pyramid methods in image processing","volume":"29","author":"Adelson E. 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