Abstract: An MERF based edge detection algorithm with adaptive threshold is presented in this paper. After analyzing dyadic wavelet transform and different behavior of edge and noise across scales, a Multi-scale Edge Response Function (MERF) is defined as the multiple scales point-wise products of the DWT to enhance significant image structures and suppress noise. Thereafter, an adaptive threshold for MERF is calculated and imposed on the module of MERF to identify edges as the local maxima of the gradient map without synthesizing the edge maps at several scales together, which was employed in many multi-scale techniques. Experiments on synthetic benchmark and natural images showed that the proposed MERF based adaptive threshold edge detection algorithm achieves better detection results than that for a single scale, especially on the localization performance; and edge and noise can be better distinguished by MERF comparing with the Laplacian of Gaussian (LOG), Canny edge detection and Mallat wavelet based edge detection algorithms.