The invention discloses an empirical-mode-decomposition-based edge detecting method, which mainly solves the problems that a clear and complete image edge cannot be well detected and a great number of false edges exist in a noise environment in the prior art. The method is technically characterized by comprising the following steps of: (1) acquiring the maximum value envelope and the minimum value envelope of an image by solving two partial differential equations during empirical mode decomposition; (2) acquiring the mean envelope and the differential envelope of the image through the maximumvalue envelope and the minimum value envelope of the image; (3) continuously iterating the step (1) and the step (2) until an iteration stopping condition is met so as to acquire the inherent mode function of the image and the residual image; and (4) calculating the gradient and the threshold of the acquired residual image by using two Prewitt operators so as to acquire the edge of the image. Compared with the traditional Prewitt operator and Canny operator, the method has the advantages that: the clearer and more complete image edge can be acquired, and the influence of the false edges and noise on edge detection is reduced simultaneously.