The Multi-Scale Veto Model: A Two-Stage Analog Network for Edge Detection and Image Reconstruction

Abstract

This paper presents the theory behind a model for a two-stage analog network for edge detection and image reconstruction to be implemented in VLSI. Edges are detected in the first stage using the multi-scale veto rule, which eliminates candidates that do not pass a threshold test at each of a set of different spatial scales. The image is reconstructed in the second stage from the brightness values adjacent to edge locations. The MSV rule allows good localization and efficient noise removal. Since the reconstructed images are visually similar to the originals, the possibility exists of achieving significant bandwidth compression.