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		<doi>10.1109/SIBGRAPI.2009.13</doi>
		<citationkey>PaixãoPLLPTLL:2009:RaWaVe</citationkey>
		<title>Random Walks for Vector Field Denoising</title>
		<format>Printed, On-line.</format>
		<year>2009</year>
		<numberoffiles>1</numberoffiles>
		<size>7357 KiB</size>
		<author>Paixão, João,</author>
		<author>Petronetto, Fabiano,</author>
		<author>Lage, Marcos,</author>
		<author>Laier, Alex,</author>
		<author>Pesco, Sinésio,</author>
		<author>Tavares, Geovan,</author>
		<author>Lewiner, Thomas,</author>
		<author>Lopes, Hélio,</author>
		<affiliation>Matmídia Laboratory – Department of Mathematics, PUC–Rio – Rio de Janeiro, Brazil</affiliation>
		<affiliation>Matmídia Laboratory – Department of Mathematics, PUC–Rio – Rio de Janeiro, Brazil</affiliation>
		<affiliation>Matmídia Laboratory – Department of Mathematics, PUC–Rio – Rio de Janeiro, Brazil</affiliation>
		<affiliation>Matmídia Laboratory – Department of Mathematics, PUC–Rio – Rio de Janeiro, Brazil</affiliation>
		<affiliation>Matmídia Laboratory – Department of Mathematics, PUC–Rio – Rio de Janeiro, Brazil</affiliation>
		<affiliation>Matmídia Laboratory – Department of Mathematics, PUC–Rio – Rio de Janeiro, Brazil</affiliation>
		<affiliation>Matmídia Laboratory – Department of Mathematics, PUC–Rio – Rio de Janeiro, Brazil</affiliation>
		<affiliation>Matmídia Laboratory – Department of Mathematics, PUC–Rio – Rio de Janeiro, Brazil</affiliation>
		<editor>Nonato, Luis Gustavo,</editor>
		<editor>Scharcanski, Jacob,</editor>
		<e-mailaddress>lewiner@gmail.com</e-mailaddress>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 22 (SIBGRAPI)</conferencename>
		<conferencelocation>Rio de Janeiro, RJ, Brazil</conferencelocation>
		<date>11-14 Oct. 2009</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>Discrete Vector Field, Denoising, Random Walk, Markov Chain.</keywords>
		<abstract>In recent years, several devices allow to directly  measure real vector &#64257;elds, leading to a better understanding of fundamental phenomena such as &#64258;uid simulation or brain water movement. This turns vector &#64257;eld 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 &#64257;eld analysis. This paper proposes a novel method for vector &#64257;eld 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.</abstract>
		<language>en</language>
		<targetfile>57789_2.pdf</targetfile>
		<usergroup>lewiner@gmail.com</usergroup>
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