基于曲波变换和Susan种子点生长的边缘检测算法OA北大核心CSCDCSTPCD
An image edge detection algorithm based on curvelet transform and Susan seed point-growth
针对现存的基于空间域的图像边缘检测算法只能有效检测出图像有限方向边缘以及对于纹理复杂的图像边缘定位困难等问题,提出了一种基于曲波变换和Susan种子点生长的边缘检测算法,该算法首先对源图像进行曲波变换,然后对高频子图像运用Susan种子点生长算法进行边缘提取；对低频子图像采用极大值方法将轮廓检测出来,最后通过一定的融合规则进行融合,得到边缘图.理论和实验结果表明,该算法具有较高的效率和很好的抗噪声能力,尤其对具有复杂纹理的图像是一种有效的边缘检测方法.
The available image edge detection algorithm based on the spatial-domain can capture only limited directional edge in image. An improved algorithm for the image edge detection based on the directions of each directional sub-band and its gradient is proposed to overcome the disadvantages. By the algorithm, firstly, multi-scale decomposition of the image is performed by curvelet transform. Then the edge detection of low-frequency sub-image and high-frequency s…查看全部>>
张瑞华;吴谨
中国人民解放军空军雷达学院实验中心,武汉430019武汉科技大学信息科学与工程学院,武汉430081
信息技术与安全科学
边缘检测曲波变换Susan算子角点提取种子点
edge detection curvelet transform Susan operator corner detection seed point
《华中师范大学学报（自然科学版）》 2011 (3)
386-390,411,6
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