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本文提出一种新的用于散斑噪音压缩的并行组合加权均值级联形态滤波算法．首先采用3×1和1×3两个线型结构元素分别进行形态开一闭、闭一开运算，然后利用散斑噪音的负指数统计规律加权求平均，最后再采用5×1和1×5两个线型结构元素重复上述运算．模拟结果表明此算法既有效地压缩了散斑噪音又保持了图象的几何结构，并且通过比较证明其优于F．Safa的多方向形态滤波算法．
In this paper, a new parallel combined weighted mean cascade morphological filtering algorithm for speckle noise compression is proposed. Firstly, the two linear structure elements of 3 × 1 and 1 × 3 are used to form a closed form and an open form, respectively, and then weighted averaged by the negative exponential statistical rule of speckle noise. Finally, 5 × 1 and 1 × 5 The two linear structure elements repeat the above operation. The simulation results show that this algorithm not only effectively reduces the speckle noise but also preserves the geometric structure of the image, which is proved to be better than F by comparison. Safa multi-directional morphological filtering algorithm.