Synthetic aperture radar image processing using Cellular Neural Networks


Kent S. , UCAN O. N. , ENSARI T.

International Conference on Recent Advances in Space Technologies, İstanbul, Turkey, 20 - 22 November 2003, pp.308-310 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.308-310

Abstract

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.