Abstract: A new method is proposed for speckle noise suppression and water objects extracting from Synthetic Aperture Radar（SAR） imagery based on sequential nonlinear filtering and Blind Signal Separation（BSS）.The distribution of SAR image data with multiplicative speckle noise is non-Gausssian and its parameters are unknown.Logarithmic quantification is utilized to transform multiplicative speckle noise to independent additive noise.Speckle noise and image data are separated from multi-polarimetric imagery，and the components with the least speckle index are chosen as the object component automatically by means of BSS while the specific distribution of SAR imagery is unnecessary.Water objects are extracted from the separated object component imagery based on sequential nonlinear filtering according to their lightness and region shape features.The experimental results using ENVISAT ASAR polarimetric imagery show that the proposed method can extract water objects rapidly and accurately.

Key words: polarimetric synthetic aperture radar imagery, water objects, automatic recognition, blind signal separation, sequential nonlinear filtering

摘要： 采用一种新的基于盲信号分离（BSS）和序列非线性滤波方法实现多极化合成孔径雷达（SAR）影像相干斑噪声抑制和水体目标快速提取。SAR影像具有强烈乘性相干斑噪声，影像数据为非高斯分布，但其具体分布形式及参数难以获得。利用基于独立分量分析的盲信号分离方法，不需要知道SAR影像的具体分布，通过对数量化将相干斑噪声转化为与图像数据相互独立的加性噪声，从多极化SAR影像中自动分离出图像数据与相干斑噪声，并自动选择相干斑指数最小的分量为图像分量。针对SAR影像水体目标的亮度及形状分布特征，进一步采用序列非线性滤波处理，从分离出的图像分量中提取出水体目标。利用ENVISAT ASAR多极化影像进行了实验，结果表明该方法可以快速准确地提取多极化SAR影像中的水体目标。

关键词: 极化合成孔径雷达影像, 水体目标, 自动识别, 盲信号分离, 序列非线性滤波