Wang Bo, Pan Quan, Zhang Hongcai, Dai Guanzhong. THE FEATURE ANALYSIS OF IMAGE EDGE DETECTION WITH WAVELETS[J]. Journal of Electronics & Information Technology, 1998, 20(2): 277-280.
Citation:
Wang Bo, Pan Quan, Zhang Hongcai, Dai Guanzhong. THE FEATURE ANALYSIS OF IMAGE EDGE DETECTION WITH WAVELETS[J]. Journal of Electronics & Information Technology, 1998, 20(2): 277-280.
Wang Bo, Pan Quan, Zhang Hongcai, Dai Guanzhong. THE FEATURE ANALYSIS OF IMAGE EDGE DETECTION WITH WAVELETS[J]. Journal of Electronics & Information Technology, 1998, 20(2): 277-280.
Citation:
Wang Bo, Pan Quan, Zhang Hongcai, Dai Guanzhong. THE FEATURE ANALYSIS OF IMAGE EDGE DETECTION WITH WAVELETS[J]. Journal of Electronics & Information Technology, 1998, 20(2): 277-280.
A quantitative analysis on the local precision and the ability against noise for image edge detection with wavelets (IEDW) has been done in this paper. With an appropriate wavelet function, IEDW algorithm is equal with a process that consists of two child processes: denoising and edge detecting. The feature is relative to the type of edges and the scales. The influence of the scale is a morror of the local feature of wavelet transform.
秦前清,扬中凯.实用小波分析.西安:西安电子科技大学出版社,1994, 80-92.[2]吴立德.计算机视觉.上海:上海复旦大学出版社,1992, 20-33.[3]Mallat S. A theory for multiresolution signal decomposition: The wavelet representation. IEEE Trans. on Pattern and Machine Intelligence, 1989, PAMI-11(7): 674-692.[4]Mallat S, Zhong S. Characterizaton of signals from multiscale edges. IEEE Trans. on Pattern and Machine Intelligence, 1992, PAMI-14(7): 710-731.
DownLoad: