Edge detection combining wavelet transform and canny operator based on fusion rules

Abstract

Aiming for the problem of discarding some important details of high-frequency sub-image when detecting the edge based on wavelet transform, and the effect of edge extracting is poor because of the noise influence. This paper proposed a new fusion algorithm based on wavelet transform and canny operator to detect image edges. In the wavelet domain, the low-frequency sub-image edges are detected by canny operator, while the high-frequency sub-image are detected by solving the maximum points of local wavelet coefficient model to restore edges after reducing the noise by wavelet. Then, both sub-images edges are fused according to certain rules. Experiment results show the proposed method can detect image edges not only remove the noise effectively but also enhance the edges and locate edges accurately.