提出一种基于目标及背景结构特征的多尺度形态学图像处理方法,针对弱目标和背景噪声的结构差异,选择合适的结构元素和合理的形态算子达到较好的滤波效果.形态滤波器是从数学形态学中发展出来的一类新型非线性滤波器.由于形态算子实质上是表达物体或形状的集合与结构元素之间的相互作用,结构元素的形态决定了这种运算所提取的信号的形态信息,因此数学形态学对信号的处理具有直观上的简单性和数学上的严谨性,使数学形态学在描述信号形态特征上具有独特的优势.通过改变结构基元的尺度,对图像进行多尺度分析,能准确提取图像在不同尺度下形状的分层特征和有用信息.

An image processing method based on the multi-scale morphology which focuses on the structural difference between dim target and background noise is presented. A better filtering effect can be got by choosing proper structure elements and morphological operators. The morphological filter is a new type of nonlinear filter developed from mathematical morphology. Structural information distilled from signal by use of morphological operation is determined by the form of structure element, since morphological operators in essence show the reciprocity between the aggregation of targets and structure element. Because of the mathematical preciseness and the simpleness, there is a particular advantage of mathematical morphology when it is used to describe the configurative characteristic of target image. The useful information and multi-level features from the images can be got by multi-scale analysis using morphological filters through changing the scale parameter of the structure elements.