Texture is considered as one of the most crucial image features used commonly in computer vision. It is important source of information about image content, especially for single-band images. In this paper we present the results of research carried out to assess the usefulness of selected textural features of different groups in panchromatic very high resolution (VHR) satellite image classification. The study is based on images obtained from EROS A satellite. The aim of our tests was to estimate and compare the accuracy of main land cover types classification, with a particular focus on determining usefulness of textural features based on multifractal formalism. Presented research confirmed that it is possible to use the textural features as efficient global descriptors of VHR satellite image content. It was also prove that multifractal parameters should be considered as valuable textural features in the context of land cover classification.
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