A Novel Filtering Algorithm for SAR Image Based on Self Adaptive Correction of Penalty Coefficient
Zhensong Wang, Xiaoyun Liu, Wufan Chen, Xiaowen Li · 2006
Speckle noise is much serious in SAR (synthetic aperture radar) image. It will seriously affect the information extraction of terra and object and the application of SAR image. A novel filtering algorithm for speckle noise in SAR image is presented here. This algorithm is based on an iterative filter that based on a membrane model Markov random field approximation optimized by a synchronous local iterative method (TSPR). With this algorithm, the affect of the energy function by neighbors' spatial relation is taken into account. By self adaptive correcting the penalty coefficient in iteration process better filtering effect can be acquired. According to the comparing experiments about faded image by speckle noise of various intensities, with the algorithm presented here we can get restored image with higher signal noise ratio (SNR) than TSPR