The usefulness of wavelet-based features as global descriptors of VHR satellite images

Krystian Pyka; Wojciech Drzewiecki; Katarzyna Bernat; Anna Wawrzaszek; Michal Krupiński

doi:10.1117/12.2067323

13 October 2014 Usefulness of wavelet-based features as global descriptors of VHR satellite images

Krystian Pyka, Wojciech Drzewiecki, Katarzyna Bernat, Anna Wawrzaszek, Michal Krupiński

Author Affiliations +

Proceedings Volume 9244, Image and Signal Processing for Remote Sensing XX; 92441D (2014) https://doi.org/10.1117/12.2067323
Event: SPIE Remote Sensing, 2014, Amsterdam, Netherlands

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.

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Krystian Pyka, Krystian Pyka, Wojciech Drzewiecki, Wojciech Drzewiecki, Katarzyna Bernat, Katarzyna Bernat, Anna Wawrzaszek, Anna Wawrzaszek, Michal Krupiński, Michal Krupiński, "Usefulness of wavelet-based features as global descriptors of VHR satellite images", Proc. SPIE 9244, Image and Signal Processing for Remote Sensing XX, 92441D (13 October 2014); doi: 10.1117/12.2067323; https://doi.org/10.1117/12.2067323

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