A Nagao-Matsuyama approach to high-resolution satellite image classification

Author

Baraldi, A. ; Parmiggiani, F.

Author_Institution

IMGA-CNR, Modena, Italy

Volume

32

Issue

4

fYear

1994

fDate

7/1/1994 12:00:00 AM

Firstpage

749

Lastpage

758

Abstract

A knowledge-based, hierarchical, unsupervised classification scheme for high-resolution multispectral satellite (HRMS) images is described. This scheme, which finds its conceptual bases in the work of Nagao and Matsuyama for structural analysis of aerial photographs, introduces a new filtering algorithm which is able to preserve fine linear structures of the image. An example of the application of this classification scheme to a Landsat Thematic Mapper multispectral image is presented

Keywords

edge detection; feature extraction; geophysical techniques; geophysics computing; image recognition; knowledge based systems; optical information processing; remote sensing; Landsat Thematic Mapper multispectral image; Nagao Matsuyama approach; feature extraction; filtering algorithm; fine linear structure; geophysical measurement technique; hierarchical unsupervised classification; high-resolution; knowledge-based; land surface; multispectral method; optical imaging; remote sensing; satellite image classification; visible infrared IR; Algorithm design and analysis; Filtering algorithms; Focusing; Human resource management; Image analysis; Image classification; Image sensors; Remote sensing; Satellite broadcasting; Spatial resolution;

fLanguage

English

Journal_Title

Geoscience and Remote Sensing, IEEE Transactions on

Publisher

ieee

ISSN

0196-2892

Type

jour

DOI

10.1109/36.298004

Filename

298004