Multiresolution edge detection

The neural network implementation of some commonly used edge detectors is reviewed and compared. Edge detection is scale-dependent. Edges are visible only over a range of scales. Multiple scale analysis of the input image is required to have a complete description of the edges. The authors propose a compact pyramidal multi-level neural net architecture for image representation at multiple spatial scales. Lateral weighted links within a level compute edge localization and intensity gradient. Feedback between successive levels is used to reinforce and refine the position of true edges