{"id":8543,"date":"2012-11-22T23:54:38","date_gmt":"2012-11-22T21:54:38","guid":{"rendered":"http:\/\/hgpu.org\/?p=8543"},"modified":"2012-11-22T23:54:38","modified_gmt":"2012-11-22T21:54:38","slug":"gpu-implementation-of-fuzzy-anisotropic-diffusion","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=8543","title":{"rendered":"GPU Implementation of Fuzzy Anisotropic Diffusion"},"content":{"rendered":"<p>In this paper, we present a GPU-based implementation of the Fuzzy-Anisotropic diffusion technique oriented for high-resolution multidimensional image\/video techniques. The aggregation of parallel computing and the HW\/SW co-design techniques are used in order to improve the time performance of the Fuzzy-Anisotropic Diffusion algorithm for image\/video applications. Experimental results show the significantly increased performance efficiency both in resolution enhancement and in computational complexity reduction metrics gained with the proposed approach.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this paper, we present a GPU-based implementation of the Fuzzy-Anisotropic diffusion technique oriented for high-resolution multidimensional image\/video techniques. The aggregation of parallel computing and the HW\/SW co-design techniques are used in order to improve the time performance of the Fuzzy-Anisotropic Diffusion algorithm for image\/video applications. Experimental results show the significantly increased performance efficiency both [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[36,89,33,3],"tags":[1787,14,1786,20,1226],"class_list":["post-8543","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-nvidia-cuda","category-image-processing","category-paper","tag-algorithms","tag-cuda","tag-image-processing","tag-nvidia","tag-tesla-c2075"],"views":2557,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8543","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=8543"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8543\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8543"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=8543"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=8543"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}