We detected edges in noisy images using multiresolution analysis with the wavelet transform. products of wavelet coefficients at several scales were used to identify and locate edges. We found that it was important to consider the changes in edge position at different scales to detect edges in noisy imagery. We analyzed one-dimensional edges and compared the results of our approach with the first derivative of the signal. In addition, we compared the results of noisy images with another wavelet-based edge detection method. Our results led to improved edge detection in noisy images.