A speckle reduction algorithm for SAR images
Fulin Su, Jiang Wu, Ge Hongtao, Zhu Yong · 2002
In this paper, we propose a speckle reduction algorithm for radar images based on the wavelet transform. First, the logarithmic transform is applied to the original image to convert the multiplicative noise model into an additive Gaussian noise model. Then multiscale wavelet decomposition is used to obtain pyramidal-structured subimages. A direction-dependent mask is used to identify the edges in the detail images in wavelet subspaces. These subimages are processed by reducing the amplitude of the wavelet coefficients in the detail images and releasing the amplitude where are judged edges, so that speckles are suppressed and edges are preserved. Finally, the wavelet reconstruction and exponential transformation are applied to the processed subimages and the despeckled output image is obtained. The experimental results with a JERS-1 image show that the proposed algorithm is effective in both speckle reduction and edge preservation.