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Image Processing
Wednesday, 10 August 10:45 am - 12:15 pm | East Building, Exhibit Hall A
Session Chair: Aaron Hertzmann, University of Toronto
Antialiasing Recovery
This method for restoring antialiased edges that are damaged by certain types of nonlinear image processing operations selectively adjusts the local gradients in affected regions of the filtered image so that they are consistent with those in the original image.
Lei Yang
Hong Kong University of Science and Technology
Pedro Sander
Hong Kong University of Science and Technology
Jason Lawrence
University of Virginia
Hugues Hoppe
Microsoft Research
Local Laplacian Filters: Edge-Aware Image Processing With a Laplacian Pyramid
This paper demonstrates state-of-the-art edge-aware image processing using Laplacian pyramids. The advantage of this approach is its conceptual simplicity and flexibility, based on simple point-wise nonlinearities; no optimization or post-processing is required. The method produces consistently high-quality results, without degrading edges or introducing halos.
Sylvain Paris
Adobe Systems Incorporated
Sam Hasinoff
Toyota Technological Institute at Chicago and MIT CSAIL
Jan Kautz
University College London
Domain Transform for Edge-Aware Image and Video Processing
A new approach for performing high-quality edge-preserving filtering of images and videos in real time.
Eduardo S.L. Gastal
Universidade Federal do Rio Grande do Sul
Manuel M. Oliveira
Universidade Federal do Rio Grande do Sul
Non-Rigid Dense Correspondence With Applications for Image Enhancement
A new efficient method for joint recovery of both reliable local dense correspondences and a global parametric color transformation model between two images. The paper demonstrates several applications of this method for automatic example-based enhancement of photographs that share some content.
Yoav Hacohen
The Hebrew University
Eli Shechtman
Adobe Systems Incorporated
Dan Goldman
Adobe Systems Incorporated
Dani Lischinski
The Hebrew University
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发表于 2011-9-9 14:27:21
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发表于 2011-12-23 15:24:35