Linear Optimal Filter with Minimum Mean Square Error for Synthetic Aperture Radar Images
Chongzhao Han · Xi'an Jiaotong Daxue xuebao · 2009
A linear optimal filter is proposed based on the minimum mean square error(MMSE) criterion to solve the problem that the commonly used Lee and Kuan filters for synthetic aperture radar(SAR) images have bigger filtering errors.The multiplicative noise model of speckle is expanded into both the first-order and the second-order Taylor series at the same time,and then the MMSE criterion is used to deduce a unified model of linear filters.The linear optimal filter is finally obtained-by applying the MMSE criterion again to the unified model.The linear optimal filter has the lowest filtering error and the highest filtering accuracy among all linear filters.The despeckling experiments on rural and urban SAR images show that the linear optimal filter has higher edge and fine detail preserving capacity than the Kuan filter,and has higher speckle suppression than the Lee filter.A comparison with the maximum a posteriori filter shows that the linear optimal filter has lower edge and fine detail preserving capacity,but has higher capability of speckle suppression.