Share Email Print

Proceedings Paper

Analysis of regularization edge detection in image processing
Author(s): Allen Gee; David M. Doria
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Regularization is a paradigm for performing image segmentation and edge detection, that can be implemented in a neural network type architecture. Various topics and problems pertaining to the use of regularization for image processing applications are discussed. Topics include data fusion, sensor blur, and the operation on partitioned images. A mathematical analysis of the different topics is presented, including a modification of the original regularization energy functional to perform data fusion.

Paper Details

Date Published: 16 September 1992
PDF: 11 pages
Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); doi: 10.1117/12.139987
Show Author Affiliations
Allen Gee, Hughes Aircraft Co. (United States)
David M. Doria, Hughes Aircraft Co. (United States)

Published in SPIE Proceedings Vol. 1709:
Applications of Artificial Neural Networks III
Steven K. Rogers, Editor(s)

© SPIE. Terms of Use
Back to Top