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Proceedings Paper

Neural method of spatiotemporal filter design
Author(s): Jaroslaw Szostakowski
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Paper Abstract

There is a lot of applications in medical imaging, computer vision, and the communications, where the video processing is critical. Although many techniques have been successfully developed for the filtering of the still-images, significantly fewer techniques have been proposed for the filtering of noisy image sequences. In this paper the novel approach to spatio- temporal filtering design is proposed. The multilayer perceptrons and functional-link nets are used for the 3D filtering. The spatio-temporal patterns are creating from real motion video images. The neural networks learn these patterns. The perceptrons with different number of layers and neurons in each layer are tested. Also, the different input functions in functional- link net are searched. The practical examples of the filtering are shown and compared with traditional (non-neural) spatio-temporal methods. The results are very interesting and the neural spatio-temporal filters seems to be very efficient tool for video noise reduction.

Paper Details

Date Published: 14 October 1997
PDF: 11 pages
Proc. SPIE 3167, Statistical and Stochastic Methods in Image Processing II, (14 October 1997); doi: 10.1117/12.279648
Show Author Affiliations
Jaroslaw Szostakowski, Warsaw Univ. of Technology (Poland)

Published in SPIE Proceedings Vol. 3167:
Statistical and Stochastic Methods in Image Processing II
Francoise J. Preteux; Jennifer L. Davidson; Edward R. Dougherty, Editor(s)

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