基于Q-Shift双树复小波的SAR图像相干斑噪声抑制

在复杂的SAR相干成像过程中，SAR图像会受到相干斑噪声影响，传统的图像去噪方法不能对相干斑噪声进行有效抑制，从而会严重影响SAR图像目标的提取和识别。针对SAR图像的特点，提出一种基于Q-Shift双树复小波变换（DT-CWT）的SAR图像相干斑噪声抑制方法。该方法利用Q-Shift双树复小波变换的平移不变性、多方向选择性、滤波器结构对称性等优点，对含有特征目标的含斑SAR图像进行小波系数分解，来获得更多的目标高频信息。然后通过对小波系数建模和图像重构，得到去斑SAR图像。试验结果表明，该方法对含有特征目标的SAR图像相干斑噪声有抑制效果，而且能够更好地保留图像细节和目标特征。

SAR Image Despeckling Based on Q-Shift DT-CWT

In the coherent complex SAR imaging, SAR image will be affected by speckle noise, which will seriously affect the extraction of the target. A new method of SAR image despeckling is proposed based on Q-Shift DT-CWT. Q-Shift DT-CWT has advantages of translational invariance, multi-directional selectivity, filter symmetry structure, so SAR image polluted by speckle noise can get more high frequen- cy information of goals through wavelet coefficients of decomposition. SAR despeckling images are ob- tained by modeling and image reconstruction of wavelet coefficients. Experiment results show that this method not only suppresses the speckle noise effectively, but also preserves as many target characteristics of original images as possible.