Image Recovery Using a New Nonlinear Adaptive Filter Based on Neural Networks
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Title | Image Recovery Using a New Nonlinear Adaptive Filter Based on Neural Networks |
Authors | |
Abstract | 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. |
Publisher | University of Zagreb, University Computing Centre - SRCE |
Date | 1970-01-01 |
Source | Journal of Computing and Information Technology Vol 14, No 4 (2006) |
Rights | CIT. Journal of Computing and Information Technology is an open access journal.Authors who publish with this journal agree to the following terms:Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work´s authorship and initial publication in this journal.Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal´s published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access). |