Multifractal Parameters for Spectral Profile Description

Hyperspectral data provides huge amount of detailed information about spectral properties of the objects. In the era of fast data volume enlargement, it is necessary to develop methods and algorithms which are capable for information extraction from Big Data. On the other hand, plenty of phenomena observed on Earth reveal (multi)fractal character or properties. In our work, we focus on application of multifractal formalism for remote sensing data analysis. In this paper, we present an example of multifractal parameters estimation for aerial hyperspectral dataset analyses. We have applied the Multifractal Detrended Fluctuation Analysis (MDFA) for spectral signatures description. Two main aspects of this work contain different strategies for multifractal parameters estimation and assessment of multifractal features usability in the context of hyperspectral image classification.