A novel adaptive filtering algorithm for SAR speckle reduction
Zhu Jiabing, Chen Renyuan, Hong Yi · 2007
The novel adaptive filtering algorithm based on the analysis of the detail images obtained from the wavelet decomposition of the original noisy image is proposed in the paper. The base idea is to compute the wavelet decomposition of the noisy image to reduce the amplitude of insignificant detail coefficients in the wavelet subspaces by selecting an adaptive filter window of size, the adaptive windowing algorithm was introduced where the window size is automatically adjusted depending on the samples statistics in the boundary of this window such as mean$ \bar z $and standard deviation σz, and then utilizing modified 2ndorder Lee filtering. One of the advantages of this approach over the traditional speckle filtering method is the fact that textures are preserved while speckle is reduced. Experimental simulations by real SAR images show it are effective.