A wavelet-based multiscale edge detection scheme is presented in this paper. By multiplying the wavelet coefficients at two adjacent scales to magnify significant structures and suppress noise, we determined edges as the local maxima directly in the scale product after an efficient thresholding instead of first forming the edge maps at several scales and then synthesizing them together, which was employed in many multiscale techniques. It is shown that the scale multiplication achieves better results than either of the two scales, especially on the localization performance. Experiments on natural images are compared with the Laplacian of Gaussian (LOG) and Canny edge detection algorithms.