Textural classification of high resolution digital satellite imagery

1 January 1998

conference paper
Published by Institute of Electrical and Electronics Engineers (IEEE)

Vol. 5, 2590-2592 vol.5
https://doi.org/10.1109/igarss.1998.702288

Abstract

This paper presents investigations with digital spectral and textural classification of urban environment using SPOT XS imagery and grey level co-occurrence matrix (GLCM) approach. The results indicate that a combination of texture and spectral features significantly improves the classification accuracy compared to a classification with pure spectral features only. This improvement is about 9% for an addition of one texture feature.

Keywords

IMAGE RESOLUTION
SATELLITES
STATISTICAL ANALYSIS
QUANTIZATION
RADIOMETRY
CIVIL ENGINEERING
ELECTRONIC MAIL
TESTING
PERFORMANCE EVALUATION
CITIES AND TOWNS

This publication has 1 reference indexed in Scilit:

Textural Features for Image Classification
IEEE Transactions on Systems, Man, and Cybernetics, 1973