Wavelet edge detection using two-dimensional otsu model and local enhancement

In the paper, we use wavelet technique to detect edges in small scale along the direction of gradient maximum. Edges that we extracted are accurate and single-pixel wide. But the photo also contains a lot of noise, so we set threshold to extract the ideal edge points. Currently, the threshold is set mostly by people's experience that needing a lot of trial or set the average gray value of the image directly, but the overall effect is not satisfactory. In response to the problem, we propose a method of using two-dimensional otsu model to obtain the threshold, the two-dimensional otsu method not only considers the gray value of pixels but also takes the pixels outside their fields of space-related information into account and it takes a good performance in the presence of noise of image. And we do not need to set any parameter to get the threshold. After that, we propose the corresponding solution to the problem that some edge points can not be detected: local enhancement method. In the method, we first operate the fuzzy edges of the original image, and then use the method we have proposed to detect the edges again. Finally, the simulation shows the correctness and effectiveness of the algorithm and it can also detect the fuzzy edges with an advantage of positioning accurate and having low noise.