SAR Image De-noised Based on Wavelet-Contourlet Transform with Cycle Spinning

As the synthetic aperture radar (SAR) has been widely used in agriculture, forestry, hydrology, mining, marine, mapping and other fields, the method to improve the image quality and visual effect of the SAR image has become a hot research problem for the international scholars. The suppression and removal of the speckle of SAR image has been more and more important. This paper analyzes how the noises of the SAR image are generated and their models are appropriate for the characteristics of SAR images. Then based on the advantages of wavelet transform and the Contourlet transform, we proposed a SAR image de-noising algorithm, which is Wavelet-Contourlet Transform with Cycle Spinning de-noising algorithm. The proposed algorithm can significantly suppress the speckle noise and improve the SNR of the image, also have the character of translational invariance, greatly improve the visual effect.. Compared with just using Wavelet transform, the experiment result shows that the proposed algorithm’s SNR increased 2dB. The proposed algorithm for SAR image de-noising makes the SAR images to be smoother than Contourlet transform and to be of much fewer man-made textures, the visual effects of the SAR image after de-nosing have been significant improvements.