Share Email Print
cover

Proceedings Paper

Model-based approach to Landsat Thematic Mapper (TM) scene linear lines of communication (LOC) segment detection using morphology
Author(s): Anthony H. Kahng; Kenneth A. Abeloe; Paul E. Teschan
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

This paper introduces a model based morphology technique for detecting linear segments in Landsat TM imagery. Linear segment detection has been identified as the initial step in many automated processes -- multiple image registration using linear features, lines of communication (LOC) detection, and target detection algorithms. Even though there have been many research studies aimed at the detection of linear segments in single band imagery, little research has been done on multispectral data which considers all the bands simultaneously. The fundamental idea behind this paper is to apply normal gray level image operations to multispectral imagery. Simply applying a single band edge detection algorithm to each band separately ignores the radiometric response of the edge detector. Applying morphological based operations to each band and accounting for the radiometric response of the target (i.e., LOC) pixels, one may develop a measure for the radiometric fit for each band and combine the individual band responses into a single useful output. Application of the model-based morphological filter designed in accordance with the radiometric responses of the linear segments and fusion of the results from all the bands improves linear segment detection.

Paper Details

Date Published: 8 July 1994
PDF: 12 pages
Proc. SPIE 2231, Algorithms for Multispectral and Hyperspectral Imagery, (8 July 1994); doi: 10.1117/12.179778
Show Author Affiliations
Anthony H. Kahng, GDE Systems Inc. (United States)
Kenneth A. Abeloe, GDE Systems Inc. (United States)
Paul E. Teschan, GDE Systems Inc. (United States)


Published in SPIE Proceedings Vol. 2231:
Algorithms for Multispectral and Hyperspectral Imagery
A. Evan Iverson, Editor(s)

© SPIE. Terms of Use
Back to Top