@inbook {1119, title = {Image enhancement by median filters in algebraic reconstruction methods: an experimental study}, booktitle = {Advances in Visual Computing}, series = {Lecture Notes in Computer Science}, number = {6455}, year = {2010}, note = {UT: 000290358400035ScopusID: 78650793785doi: 10.1007/978-3-642-17277-9_35}, month = {Nov-Dec 2010}, pages = {339 - 348}, publisher = {Springer Verlag}, organization = {Springer Verlag}, type = {Conference paper}, address = {Las Vegas, NV, USA}, abstract = {

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.

}, isbn = {978-3-642-17276-2}, doi = {10.1007/978-3-642-17277-9_35}, author = {Norbert Hantos and P{\'e}ter Bal{\'a}zs}, editor = {George Bebis and Richard Boyle and Bahram Parvin and Darko Koracin and Ronald Chung and Riad Hammound and Muhammad Hussain and Tan Kar-Han and Roger Crawfis and Daniel Thalmann and David Kao and Lisa Avila} }