An Algorithm Based on Wavelet-Domain Hidden Markov Models for SAR Speckle Reduction
一种基于小波域隐马尔可夫模型的SAR相干斑抑制算法

Speckle noise is an intrinsic property of Synthetic Aperture Radar (SAR) imagery. The demand for speckle reduction of SAR images is to smooth the speckle noise while preserving the structure information of the original images. Existing speckle suppression methods possess respective merits and drawbacks, without universal adaptability. Integrating the statistical characteristic of speckle noise in SAR images with wavelet domain hidden Markov models (HMMs) structure of images, we propose a new wavelet domain speckle reduction method. Simulation and experimental results using real data show that the proposed method is able to effectively suppress speckle noise and to better retain edge structure. Compared with wavelet domain soft thresholding denoising algorithm and Lee multiplicative speckle filter, the wavelet domain HMMs method offers significant improvements on smoothing speckle and preserving edge. In addition, the proposed method also gets a better visual effect.