摘要
针对传统多尺度图切割方法进行图像边缘轮廓提取时仅采用高斯低通滤波和一阶微分求导,而忽略轮廓精度的缺陷,提出利用二进小波变换的方法进行多尺度边缘检测。在建立多尺度相似矩阵的过程中,根据每层小波的特性直接对各个尺度的相似矩阵进行构造,有效地减少了求解相似矩阵的运算复杂度,降低了内存消耗。实验结果表明,该方法与传统多尺度图切割方法相比具有更好的分割效果。
Aiming at the default that when the traditional multi-scale ncut algorithm is applied to image edge detection,it only uses the Gaussian low-pass filtering and derivative derivation to extract contour and ignores the accuracy of contour,this paper presents that using dyadic wavelet transform to detect multi-scale edge.In the multi-scale weight matrix constructing process,using the feature of each wavelet to solve similarity matrix,it greatly reduces the computational complexity to solve similarity matrix and reduces the memory consumption.Experimental results prove that proposed algorithm obtains better segmentation results than the traditional multiscale Ncut algorithm.
出处
《计算机工程与应用》
CSCD
北大核心
2015年第13期9-14,共6页
Computer Engineering and Applications
基金
国家自然科学基金(No.51265018
No.60962007
No.61302173
No.61461022)
云南省自然科学基金(No.2012FB129)
云南省教育厅研究基金重大专项(No.ZD2013004)
