Image spatial diffusion targets on blurring small discontinuities while sharpening distinct edges. We propose two GPU-based methods to efficient generate content-aware spatial diffused images. In the first method, we apply an enhanced bilateral filter on the input image. Our filter adopts a spatial weight kernel in the form of an inverted Gaussian. This inverted-Gaussian-spatial bilateral filter (IGSB) can remove small spots in large smooth areas more efficiently than Gaussian bilateral filter that are commonly used. In the second method, we present a fast approximation of mean-shift algorithm on GPUs. Considering the parallel nature of GPUs, the process of mean-shift kernel density estimation is modified and improved to achieve satisfied color image diffusion effects.<\/p>\n","protected":false},"excerpt":{"rendered":"
Image spatial diffusion targets on blurring small discontinuities while sharpening distinct edges. We propose two GPU-based methods to efficient generate content-aware spatial diffused images. In the first method, we apply an enhanced bilateral filter on the input image. Our filter adopts a spatial weight kernel in the form of an inverted Gaussian. This inverted-Gaussian-spatial bilateral […]<\/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":[33,3],"tags":[444,841,1786,20,671,182],"class_list":["post-4823","post","type-post","status-publish","format-standard","hentry","category-image-processing","category-paper","tag-cg","tag-filtering","tag-image-processing","tag-nvidia","tag-nvidia-geforce-8500-gt","tag-opengl"],"views":2527,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4823","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=4823"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4823\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4823"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4823"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4823"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}