<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Norbert Hantos</style></author><author><style face="normal" font="default" size="100%">Péter Balázs</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">George Bebis</style></author><author><style face="normal" font="default" size="100%">Richard Boyle</style></author><author><style face="normal" font="default" size="100%">Bahram Parvin</style></author><author><style face="normal" font="default" size="100%">Darko Koracin</style></author><author><style face="normal" font="default" size="100%">Ronald Chung</style></author><author><style face="normal" font="default" size="100%">Riad Hammound</style></author><author><style face="normal" font="default" size="100%">Muhammad Hussain</style></author><author><style face="normal" font="default" size="100%">Tan Kar-Han</style></author><author><style face="normal" font="default" size="100%">Roger Crawfis</style></author><author><style face="normal" font="default" size="100%">Daniel Thalmann</style></author><author><style face="normal" font="default" size="100%">David Kao</style></author><author><style face="normal" font="default" size="100%">Lisa Avila</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Image enhancement by median filters in algebraic reconstruction methods: an experimental study</style></title><secondary-title><style face="normal" font="default" size="100%">Advances in Visual Computing</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science</style></tertiary-title><short-title><style face="normal" font="default" size="100%">LNCS</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2010</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Nov-Dec 2010</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">6455</style></number><publisher><style face="normal" font="default" size="100%">Springer Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">Las Vegas, NV, USA</style></pub-location><pages><style face="normal" font="default" size="100%">339 - 348</style></pages><isbn><style face="normal" font="default" size="100%">978-3-642-17276-2</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;div class=&quot;abstract-content formatted&quot; itemprop=&quot;description&quot;&gt;&lt;p class=&quot;a-plus-plus&quot;&gt;Algebraic methods for image reconstruction provide good solutions even if only few projections are available. However, they can create noisy images if the number of iterations or the computational time is limited. In this paper, we show how to decrease the effect of noise by using median filters during the iterations. We present an extensive study by applying filters of different sizes and in various times of the reconstruction process. Also, our test images are of different structural complexity. Our study concentrates on the ART and its discrete variant DART reconstruction methods.&lt;/p&gt;&lt;/div&gt;&lt;p&gt;&amp;nbsp;&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type><notes><style face="normal" font="default" size="100%">UT: 000290358400035ScopusID: 78650793785doi: 10.1007/978-3-642-17277-9_35</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Péter Balázs</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">George Bebis</style></author><author><style face="normal" font="default" size="100%">Richard Boyle</style></author><author><style face="normal" font="default" size="100%">Bahram Parvin</style></author><author><style face="normal" font="default" size="100%">Darko Koracin</style></author><author><style face="normal" font="default" size="100%">Paolo Remagnino</style></author><author><style face="normal" font="default" size="100%">Fatih Porikli</style></author><author><style face="normal" font="default" size="100%">Jörg Peters</style></author><author><style face="normal" font="default" size="100%">James Klosowski</style></author><author><style face="normal" font="default" size="100%">Laura Arns</style></author><author><style face="normal" font="default" size="100%">Yu Ka Chun</style></author><author><style face="normal" font="default" size="100%">Theresa-Marie Rhyne</style></author><author><style face="normal" font="default" size="100%">Laura Monroe</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Reconstruction of binary images with few disjoint components from two projections</style></title><secondary-title><style face="normal" font="default" size="100%">Advances in Visual Computing</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science</style></tertiary-title><short-title><style face="normal" font="default" size="100%">LNCS</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Dec 2008</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">5359</style></number><publisher><style face="normal" font="default" size="100%">Springer Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">Las Vegas, NV, USA</style></pub-location><pages><style face="normal" font="default" size="100%">1147 - 1156</style></pages><isbn><style face="normal" font="default" size="100%">978-3-540-89645-6</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We present a general framework for reconstructing binary imageswith few disjoint components from the horizontal and vertical projections. We develop a backtracking algorithm that works for binary images having components from an arbitrary class. Thus, a priori information about the components of the image to be reconstructed can be incorporated into the reconstruction process. In addition, we can keep control over the number of components which can increase the speed and accuracy of the reconstruction. Experimental results are also presented. © 2008 Springer Berlin Heidelberg.&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Conference paper</style></work-type><notes><style face="normal" font="default" size="100%">UT: 000262709700114ScopusID: 70149090157doi: 10.1007/978-3-540-89646-3_114</style></notes></record></records></xml>