Directional Multiscale Edge Detection Using the Contourlet Transform

摘要：

Wavelet multiresolution analysis allows us to detect edges at different scales, also to obtain other important aspects of the extracted edges. However, due to the usual two-dimensional tensor product, wavelet transform is not optimal for representing images. The main problem in edge detection using wavelet transform is that it can only capture pointsingularities, and the extracted edges are not continuous. In order to solve that problem, we propose a new image edge detection method based on the contourlet transform. The directional multiresolution representation Contourlet takes advantages of the intrinsic geometrical structure of images, and is appropriate for the analysis of the image edges. Using the modulus maxima detection, an image edge detection method based on contourlet transform is proposed. To suppress the image noise effect on edge detection, the scale multiplication in contourlet domain is also proposed. Through real images experiments, the proposed edge detection methods performance for the extracted edges is analyzed and compared with other two edge detection methods. The experiment result proves that the proposed edge detection method improves over waveletbased techniques and Canny detector, and also works well for noisy images.

关键词： wavelet multiscale edge detection contourlet modulus maxma the scale multiplication

作者: Shun-feng Ma Geng-feng Zheng Long-xu Jin Shun-feng Ma Geng-feng Zheng

作者单位: Shuang-H Han, Ran-feng Zhang Institute of Optics, Fine Mechanics and Physics Chinese Academy of Scie Graduate University Chinese Academy of Sciences Beijing, China

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 58-62

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）