一种平稳小波方向能量阈值滤波的SAR图像去噪方法

A SAR Image Denoising Method Based on Stationary Wavelet Directional Energy Threshold Filtering

由于SAR图像相干斑噪声是非高斯分布的,无法直接采用光学成像系统的去噪技术处理,因此,目前还没有真正的理想算法广泛适用于SAR图像去噪。在分析目前流行的空频域去噪方法优缺点的基础上,提出了1种小波域SAR图像去噪方法。为了克服离散小波变换缺乏平移不变性及方向选择性受限的缺点,该方法利用平稳小波将图像分解为低频逼近信号和高频细节信号;对于噪声信息较少的逼近信号,利用增强Lee滤波去噪;对细节信号,根据相干斑噪声在小波域的方向能量特性进行自适应的阈值滤波;最后重建去噪后的SAR图像。实验表明,该方法去噪能力强,同时边缘保持较好。

As the coherent speckle noise of SAR images is non-Gaussian distribution,it cannot be directly processed by the denoising technology of optical imaging system.At present,there is no real ideal algorithm that can be widely used in SAR image denoising.Based on the analysis of the advantages and disadvantages of current popular space-frequency domain denoising methods,this paper proposes a wavelet domain SAR image denoising method.In order to overcome the shortcomings of discrete wavelet transforms,such as lack of translation invariance and limited direction selectivity,this method uses stationary wavelet transform to decompose the image into low-frequency approximation signals and high-frequency detail signals.For the approximation signals with less noise information,enhanced Lee filter is used to denoise;for the detail signal,adaptive threshold filtering is carried out according to the directional energy characteristics of speckle noise in wavelet domain.Finally,the denoised SAR image is reconstructed.Experiments results show that the method has strong denoising ability and good edge preservation.