{"id":615,"date":"2025-07-15T18:43:29","date_gmt":"2025-07-15T18:43:29","guid":{"rendered":"https:\/\/ccds.ai\/?p=615"},"modified":"2025-08-10T18:15:11","modified_gmt":"2025-08-10T18:15:11","slug":"non-rigid-distortion-removal-via-coordinate-based-image-representation","status":"publish","type":"post","link":"https:\/\/ccds.ai\/?p=615","title":{"rendered":"Non-Rigid Distortion Removal via Coordinate Based Image Representation"},"content":{"rendered":"<div id='av_section_1'  class='avia-section av-bvcqf-29ed692b5d02f3ed9f1b435e73663c10 main_color avia-section-default avia-no-border-styling  avia-builder-el-0  avia-builder-el-no-sibling  avia-bg-style-scroll container_wrap fullsize'  ><div class='container av-section-cont-open' ><main  role=\"main\" itemprop=\"mainContentOfPage\"  class='template-page content  av-content-full alpha units'><div class='post-entry post-entry-type-page post-entry-615'><div class='entry-content-wrapper clearfix'>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-md4vrjmh-9a53ff03659eba7c6702479e156c5121\">\n.avia-image-container.av-md4vrjmh-9a53ff03659eba7c6702479e156c5121 img.avia_image{\nbox-shadow:none;\n}\n.avia-image-container.av-md4vrjmh-9a53ff03659eba7c6702479e156c5121 .av-image-caption-overlay-center{\ncolor:#ffffff;\n}\n<\/style>\n<div  class='avia-image-container av-md4vrjmh-9a53ff03659eba7c6702479e156c5121 av-styling- avia-align-center  avia-builder-el-1  el_before_av_textblock  avia-builder-el-first '   itemprop=\"image\" itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/ImageObject\" ><div class=\"avia-image-container-inner\"><div class=\"avia-image-overlay-wrap\"><img fetchpriority=\"high\" fetchpriority=\"high\" decoding=\"async\" class='wp-image-616 avia-img-lazy-loading-not-616 avia_image ' src=\"https:\/\/ccds.ai\/wp-content\/uploads\/2025\/07\/Non-Rigid-Distortion-Removal-via-Coordinate-Based-Image-Representation.gif\" alt='' title='Non-Rigid-Distortion-Removal-via-Coordinate-Based-Image-Representation'  height=\"123\" width=\"512\"  itemprop=\"thumbnailUrl\"  \/><\/div><\/div><\/div>\n<section  class='av_textblock_section av-md4vgc1f-0aa98dae209e203cd5dbc4c336010137'  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock'  itemprop=\"text\" ><p>maging through turbulent refractive medium (e.g., hot air, in-homogeneous gas, fluid flow) is challenging, since the non-linear light transport through the medium (e.g. refraction and scattering) causes non-rigid distortions in perceived images. However, most computer vision algorithms rely on sharp and distortion-free images to achieve the expected performance. Removal of these non-rigid image distortions is therefore critical and beneficial for many vision applications, from segmentation to recognition. To resolve the distortion and blur introduced by air turbulence, conventional turbulence restoration methods leverage optical flow, regions fusion and blind deconvolution to recover images. One avenue that is underexplored for this problem is the use of coordinate based image representations. These methods represent images as the parameters of a neural network ,and they can be used to deform the image grid itself to account for turbulence. In this research, we aim to extend this idea to unseen images with meta learning that can remove both air and water distortions without much customization.<\/p>\n<p><b>Related publications:<\/b><\/p>\n<ol>\n<li aria-level=\"1\">Unsupervised Non-Rigid Image Distortion Removal via Grid Deformation, ICCV 2021<\/li>\n<\/ol>\n<\/div><\/section>\n\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":2,"featured_media":616,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[88],"tags":[],"class_list":["post-615","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai_ml_projects"],"acf":[],"jetpack_featured_media_url":"https:\/\/ccds.ai\/wp-content\/uploads\/2025\/07\/Non-Rigid-Distortion-Removal-via-Coordinate-Based-Image-Representation.gif","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/posts\/615","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/ccds.ai\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=615"}],"version-history":[{"count":5,"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/posts\/615\/revisions"}],"predecessor-version":[{"id":621,"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/posts\/615\/revisions\/621"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/media\/616"}],"wp:attachment":[{"href":"https:\/\/ccds.ai\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=615"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ccds.ai\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=615"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ccds.ai\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=615"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}