Share Email Print
cover

Proceedings Paper

The usefulness of wavelet-based features as global descriptors of VHR satellite images
Author(s): Krystian Pyka; Wojciech Drzewiecki; Katarzyna Bernat; Anna Wawrzaszek; Michal Krupiński
Format Member Price Non-Member Price
PDF $17.00 $21.00
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

In this paper we present the results of research carried out to assess the usefulness of wavelet-based measures of image texture for classification of panchromatic VHR satellite image content. The study is based on images obtained from EROS-A satellite. Wavelet-based features are calculated according to two approaches. In first one the wavelet energy is calculated for each components from every level of decomposition using Haar wavelet. In second one the variance and kurtosis are calculated as mean values of detail components with filters belonging to the D, LA, MB groups of various lengths. The results indicate that both approaches are useful and complement one another. Among the most useful wavelet-based features are present not only those calculated with short or long filters, but also with the filters of intermediate length. Usage of filters of different type and length as well as different statistical parameters (variance, kurtosis) calculated as means for each decomposition level improved the discriminative properties of the feature vector consisted initially of wavelet energies of each component.

Paper Details

Date Published: 13 October 2014
PDF: 11 pages
Proc. SPIE 9244, Image and Signal Processing for Remote Sensing XX, 92441D (13 October 2014); doi: 10.1117/12.2067323
Show Author Affiliations
Krystian Pyka, AGH Univ. (Poland)
Wojciech Drzewiecki, AGH Univ. of Science and Technology (Poland)
Katarzyna Bernat, AGH Univ. (Poland)
Anna Wawrzaszek, Space Research Centre Polish Academy of Sciences (Poland)
Michal Krupiński, Space Research Ctr. (Poland)


Published in SPIE Proceedings Vol. 9244:
Image and Signal Processing for Remote Sensing XX
Lorenzo Bruzzone, Editor(s)

© SPIE. Terms of Use
Back to Top