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 states that an edge is significant if and only if it passes 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 the edge locations. Among the key features of this model are that edges are localized at the resolution of the smallest spatial scale without having to identify maxima in brightness gradients, while noise is removed with the efficiency of the largest scale. There are no problems of local minima, and for any given set of parameters there is a unique solution. Images reconstructed from the brightnesses adjacent to the marked edges are very similar visually to the originals. Significant bandwidth compression can thus be achieved without noticeably compromising image quality.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 1992
- Accession Number
- ADA259600
Entities
People
- Lisa Dron
Organizations
- Massachusetts Institute of Technology