{"id":155105,"date":"2020-02-20T11:36:26","date_gmt":"2001-12-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/eliminating-ghosting-and-exposure-artifacts-in-image-mosaics\/"},"modified":"2020-11-03T18:27:05","modified_gmt":"2020-11-04T02:27:05","slug":"eliminating-ghosting-and-exposure-artifacts-in-image-mosaics","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/eliminating-ghosting-and-exposure-artifacts-in-image-mosaics\/","title":{"rendered":"Eliminating Ghosting and Exposure Artifacts in Image Mosaics"},"content":{"rendered":"<div class=\"asset-content\">\n<p>As panoramic photography becomes increasingly popular, there is a greater need for high-quality software to automatically create panoramic images.  Existing algorithms either produce a rough &#8220;stitch&#8221; that cannot deal with common artifacts, or require user input.  This paper presents methods for dealing with two artifacts that often occur in practice.  Our first contribution is a method for dealing with objects that move between different views of a dynamic scene.  If such moving objects are left in, they will appear blurry and &#8220;ghosted&#8221;.  Treating such regions as nodes in a graph, we can use a vertex cover algorithm to selectively remove all but one instance of each object.  Our second contribution is a method for continuously adjusting exposure across multiple images in order to eliminate visible shifts in brightness or hue.  We compute exposure corrections on a block-by block basis, then smoothly interpolate the parameters using a spline to get spatially continuous exposure adjustment. Our enhancements, combined with previously published techniques for automatic image stitching, result in a high-quality automated stitcher that exhibits far fewer artifacts than existing software.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>As panoramic photography becomes increasingly popular, there is a greater need for high-quality software to automatically create panoramic images. Existing algorithms either produce a rough &#8220;stitch&#8221; that cannot deal with common artifacts, or require user input. This paper presents methods for dealing with two artifacts that often occur in practice. Our first contribution is a [&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":"szeliski"},{"type":"user_nicename","value":"mattu"}],"msr_publishername":"IEEE Computer Society","msr_publisher_other":"","msr_booktitle":"IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'2001)","msr_chapter":"","msr_edition":"IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'2001)","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"509-516","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"II","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.  However, permission to reprint\/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org.\r\n\r\nBy choosing to view this document, you agree to all provisions of the copyright laws protecting 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