Morphological Texture Description For Hyperspectral Images: Pattern Spectrum
Peer reviewed, Journal article
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A metrological extension of morphological granulometry for the hyperspectral domain is introduced in this work. This development is enabled by the latest study of a suitable ordering relation for hyperspectral images. With granulometry as a texture descriptor, a suitable similarity measure for it is also introduced. In addition to providing validation experiments to the extension, a preliminary result in a texture discrimination task can also be found in this work.