Edge detection method based on wavelet space entropy and Canny algorithm

Wavelet space entropy is the extension of wavelet time entropy in the two-dimensional space, which can make use of the wavelet to detect sudden change in the signal. It´s a good method to eliminate the effect of noise, but at the same time, the edge it detects is coarse and not integrated. Canny operator is a classical edge detection operator that has a good localization performance for the edge. It works well for the signal mixed with little noise, but when applied to image with lots of noise, the edge it detects is often submerged by the noise. In this paper, the wavelet space entropy algorithm is improved. Furthermore, the two methods of edge detection are combined in the paper to make full use of the advantage of both methods. Simulation has proved the integrated method to be a better one for edge detection when the image is polluted by noise.