%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi@80/2009/08.17.15.44
%2 sid.inpe.br/sibgrapi@80/2009/08.17.15.44.52
%@doi 10.1109/SIBGRAPI.2009.13
%T Random Walks for Vector Field Denoising
%D 2009
%A Paixão, João,
%A Petronetto, Fabiano,
%A Lage, Marcos,
%A Laier, Alex,
%A Pesco, Sinésio,
%A Tavares, Geovan,
%A Lewiner, Thomas,
%A Lopes, Hélio,
%@affiliation Matmídia Laboratory – Department of Mathematics, PUC–Rio – Rio de Janeiro, Brazil
%@affiliation Matmídia Laboratory – Department of Mathematics, PUC–Rio – Rio de Janeiro, Brazil
%@affiliation Matmídia Laboratory – Department of Mathematics, PUC–Rio – Rio de Janeiro, Brazil
%@affiliation Matmídia Laboratory – Department of Mathematics, PUC–Rio – Rio de Janeiro, Brazil
%@affiliation Matmídia Laboratory – Department of Mathematics, PUC–Rio – Rio de Janeiro, Brazil
%@affiliation Matmídia Laboratory – Department of Mathematics, PUC–Rio – Rio de Janeiro, Brazil
%@affiliation Matmídia Laboratory – Department of Mathematics, PUC–Rio – Rio de Janeiro, Brazil
%@affiliation Matmídia Laboratory – Department of Mathematics, PUC–Rio – Rio de Janeiro, Brazil
%E Nonato, Luis Gustavo,
%E Scharcanski, Jacob,
%B Brazilian Symposium on Computer Graphics and Image Processing, 22 (SIBGRAPI)
%C Rio de Janeiro, RJ, Brazil
%8 11-14 Oct. 2009
%I IEEE Computer Society
%J Los Alamitos
%S Proceedings
%K Discrete Vector Field, Denoising, Random Walk, Markov Chain.
%X In recent years, several devices allow to directly measure real vector fields, leading to a better understanding of fundamental phenomena such as fluid simulation or brain water movement. This turns vector field visualization and analysis important tools for many applications in engineering and in medicine. However, real data is generally corrupted by noise, puzzling the understanding provided by those tools. Those tools thus need a denoising step as preprocessing, although usual denoising removes discontinuities, which are fundamental for vector field analysis. This paper proposes a novel method for vector field denoising based on random walks which preserve those discontinuities. It works in a meshless setting; it is fast, simple to implement, and shows a better performance than the traditional gaussian denoising technique.
%@language en
%3 57789_2.pdf