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		<doi>10.1109/SIBGRA.2002.1167164</doi>
		<citationkey>SalinaMascCruv:2002:CoPOAl</citationkey>
		<title>A comparison of POCS algorithms for tomographic reconstruction under noise and limited view</title>
		<year>2002</year>
		<numberoffiles>1</numberoffiles>
		<size>156 KiB</size>
		<author>Salina, Fernando V.,</author>
		<author>Mascarenhas, Nelson Delfino d'Ávila,</author>
		<author>Cruvinel, Paulo E.,</author>
		<editor>Gonçalves, Luiz Marcos Garcia,</editor>
		<editor>Musse, Soraia Raupp,</editor>
		<editor>Comba, João Luiz Dihl,</editor>
		<editor>Giraldi, Gilson,</editor>
		<editor>Dreux, Marcelo,</editor>
		<conferencename>Brazilian Symposium on Computer Graphics and Image Processing, 15 (SIBGRAPI)</conferencename>
		<conferencelocation>Fortaleza, CE, Brazil</conferencelocation>
		<date>10-10 Oct. 2002</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<organization>SBC - Brazilian Computer Society</organization>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<abstract>We present in this work a comparison among four algorithms for transmission tomography. The algorithms are based on the formalism of POCS (Projection onto Convex Sets): ART (Algebraic Reconstruction Technique), SIRT (Simultaneous Iterative Reconstruction Technique), sequential POCS and parallel POCS.  We found that the use of  adequate a priori knowledge about the solutions, expressed by convex sets restrictions, particularly in the case of the last algorithm, is an efficient way to reduce the variations on the solutions due to the ill-conditioning of  the reconstruction  problem, not only due to the noise in the projections, but also due to limited view reconstruction.</abstract>
		<language>en</language>
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		<notes>The conference was held in Fortaleza, CE, Brazil, from October 7 to 10.</notes>
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		<url>http://sibgrapi.sid.inpe.br/rep-/sid.inpe.br/banon/2002/10.24.09.28</url>
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