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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QShift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。
In complex SAR coherent imaging, SAR images are affected by speckle noise. The traditional image denoising method can not effectively suppress speckle noise, which will seriously affect the extraction and recognition of SAR images. In view of the characteristics of SAR images, a method based on QShift Double Tree Complex Wavelet Transform (DT-CWT) for SAR speckle noise suppression is proposed. This method uses the Q-Shift double-tree complex wavelet transform, such as translational invariance, multi-directional selectivity and symmetry of filter structure, to decompose wavelet-containing SAR images with feature targets to obtain more target height Frequency information. Then, the speckle SAR image is obtained by modeling the wavelet coefficients and reconstructing the image. Experimental results show that this method can restrain the speckle noise of SAR images containing feature targets and preserve the image details and target features better.