Share Email Print

Proceedings Paper

Interactive system for classifying multispectral images using a Hilbert curve
Author(s): Michiharu Niimi; Sei-ichiro Kamata; Eiji Kawaguchi
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

There are several techniques for analyzing multispectral images. In general, those are performed by linear transformation methods. In this paper, we present a new interactive method for classifying multispectral images using a Hilbert curve which is a one-to-one mapping from N- dimensional space to one dimensional space and preserves the neighborhood as much as possible. The merit of our system is that the user can extract clusters without computing any distance in N- dimensional space, and analyze multidimensional data from gross data distribution to fine data distribution hierarchically. In the experiments using LANDSAT TM data, it is confirmed that the user can get the real time response from the system after once making the data tables, and understand distribution of data that correspond to categories in feature space.

Paper Details

Date Published: 21 April 1995
PDF: 9 pages
Proc. SPIE 2501, Visual Communications and Image Processing '95, (21 April 1995); doi: 10.1117/12.206701
Show Author Affiliations
Michiharu Niimi, Nagasaki Institute of Applied Science (Japan)
Sei-ichiro Kamata, Kyushu Institute of Technology (Japan)
Eiji Kawaguchi, Kyushu Institute of Technology (Japan)

Published in SPIE Proceedings Vol. 2501:
Visual Communications and Image Processing '95
Lance T. Wu, Editor(s)

© SPIE. Terms of Use
Back to Top