MEMS microstructure image filtering based on improved SUSAN anisotropic algorithm
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摘要: 为了改善在滤除微机电系统微结构图像的噪声时导致边缘模糊的问题,提出了一种改进的各向异性SUSAN滤波算法。该方法用独立强度传播模型决定长短轴的方差,由该点的梯度方向决定滤波器的长轴方向,由局部图像的灰度值与核值的差构成的局部均值构成SUSAN滤波器的自适应阈值,从而构建出各向异性SUSAN滤波器。该算法在平滑图像同时能保持图像的边缘特征。结果表明,各向异性SUSAN滤波器能够很好地降噪并保持图像的边缘信息。Abstract: To improve the blur edge of micro electromechanical systems(MEMS) microstructures image caused by filtering the noise, an improved anisotropic SUSAN filtering algorithm was proposed. In this method, the variances of long axis and short axis were determined in accordance with the independent density spread model, the long axis direction was determined by the gradient direction of the point and the SUSAN filter threshold was determined by the partial average difference between gray value of local image and nucleus. So anisotropic SUSAN filter was constructed. The filter can maintain the edge features as well as process the image smoothing. The experimental results show that anisotropic SUSAN filter could reduce the noise and preserve the edge information at the same time.
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期刊类型引用(1)
1. 金斌英. 基于改进的SURF图像配准算法研究. 计算机测量与控制. 2019(11): 228-232 . 
百度学术
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