基于形态学和盲源分离合成孔径雷达水体提取

Method for Water Object Extraction in SAR Imagery Based on Morphology and Blind Source Separation

采用一种新的基于独立分量分析(independentcomponent analysis,ICA)盲源分离(blind source separation,BSS)和形态学开重构(open reconstruction)的方法实现多极化合成孔径雷达(synthetic aperture radar,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,具体分布形式未知.利用独立分量分析方法,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,进一步采用形态学开重构运算,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.

A new method is proposed for speckle noise suppression and water objects extracting from synthetic aperture radar （SAR）imagery based on morphology and independent component analysis （ICA） blind source 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 ICA while the specific distribution of SAR imagery is unnecessary. Water objects are extracted from the separated component imagery based on Morphology Open Reconstruction according to their lightness and region shape features. Experimental results for ENVISAT ASAR show that the method can extract water objects from the multi-polarimetric imagery with high accuracy and fast speed.