In this paper, Cellular Neural Networks (CNNs) have been applied to noisy Synthetic Aperture Radar (SAR) image to improve its performance and appearance. The image has been obtained from Erzurum, Turkey. Because of the importance of imaging quality and appearance for remote sensing applications, CNN has been applied to data for image processing applications that for noise filtering and edge detection. In training, Recurrent Perceptron Learning Algorithm (RPLA) is used as a learning algorithm. According to templates SAR-image has been tested and obtained satisfactory results.
Synthetic aperture radar image processing using cellular neural networks
01.01.2003
214047 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Synthetic Aperture Radar Image Processing Using Cellular Neural Networks
British Library Conference Proceedings | 2003
|Processing of Synthetic-Aperture-Radar Data
NTRS | 1984
|British Library Online Contents | 2004
|IEEE | 1967
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