SATELLITE IMAGES CLASSIFICATION BASED FRACTAL FEATURES

Authors

  • Laith A Al Ani Department of Physics, College of Science, Al - Nahrain University Jadiryah, Baghdad - IRAQ

Keywords:

NON

Abstract

In this paper, a TM-multi-spectral satellite images is adopted in a purpose of supervised classification. The traditional method of the segmentation namely Quad tree is applied as pre processing step. For each segmented block, the fractal features (fractal dimension and lacunarity)s are determined to be used as a maximum likelihood classifier. The results showed that the fractal dimension has not certainly able to classify the segmented blocks while the lacunarity gave good classification results. In general, the fractal geometry was found an efficient parameter for describing the image. The results show that the over all classification accuracy is 85.5%.

Published

2018-08-28

Issue

Section

Articles

How to Cite

(1)
SATELLITE IMAGES CLASSIFICATION BASED FRACTAL FEATURES. ANJS 2018, 10 (1), 79-83.