A Kalman filter using texture for noise reduction in SAR images

In this paper, we propose a noise reduction method for synthetic aperture radar (SAR) images that uses a Kalman filter. The noise in SAR images is primarily generated by speckle and appears as salt-and-pepper noise. Speckle noise is known to have the multiplicative statistical property, but this property may not hold depending on the region. Consequently, adequate noise removal is difficult. In radar, the expected values of the backscattered waves change due to the type of reflecting object. The proposed method segments an image into several regions based on the texture and varies the parameters in Kalman filtering in response to the region. By varying the parameters, the processing can account for the noise generated primarily by speckle in actual SAR images and the changes in the statistical properties of the backscattered. waves. In this paper, we apply the proposed method to synthetic test images and to actual SAR images to quantitatively evaluate the noise reduction and present the results. (C) 2003 Wiley Periodicals, Inc.