Accession Number:

ADA179945

Title:

Optimal Likelihood Generators for Edge Detection under Gaussian Additive Noise.

Descriptive Note:

Technical rept.,

Corporate Author:

ROCHESTER UNIV NY DEPT OF COMPUTER SCIENCE

Personal Author(s):

Report Date:

1986-08-01

Pagination or Media Count:

13.0

Abstract:

A technique is presented for determining the probability of an edge at a point in an image that is convolve with a linear blurring function and also with uncorrelated Gaussian additive noise. The ideal image is modeled by a set of templates for local neighborhoods. Every neighborhood in the ideal image is assumed to fit one of the templates with height probability. A computationally feasible scheme to compute the probability of edges is given. The output of several of the likelihood generators based on this model can be combined to form a more robust likelihood generator. Keywords Edge detection Template Likelihood Bayesian reasoning.

Subject Categories:

  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE