期刊名称：Journal of Computing and Information Technology
印刷版ISSN：1330-1136
电子版ISSN：1846-3908
出版年度：2006
卷号：14
期号：4
页码：315-320
出版社：SRCE - Sveučilišni računski centar
摘要：This work defines a new nonlinear adaptive filter based on a feed-forward neural network with the capacity of significantly reducing the additive noise of an image. Even though measurements have been carried out using x-ray images with additive white Gaussian noise, it is possible to extend the results to other type of images. Comparisons have been carried out with theWeiner filter because it is the most effective option for reducing Gaussian noise. In most of the cases, image reconstruction using the proposed method has produced satisfactory results. Finally, some conclusions and future work lines are presented.
