An edge detection improved algorithm based on morphology and wavelet transform

An improved edge detecting algorithm based on mathematical morphology and wavelet transform is proposed to overcome the limitation which embarrasses the performance of the traditional mathematical morphological methods. In the wavelet domain, the low-frequency sub-image edges are detected by solving the maximum points of local wavelet coefficient model to restore edges, while the high-frequency sub-image edges are detected by multi-scales and two-structuring elements mathematical morphology. Finally it can get a complete edge of the image. Experimental results showed that compared with the traditional wavelet transform edge detecting method and math morphology method, this method can adaptively extract accurate. edge information, and better decrease the noise. It is an effective edge detection method.