The pixels of remote images often contain more than one distinct material (mixed pixels),
and so their spectra are characterized by a mixture of spectral signals. Since 1971, a shared …

This article proposes a blind nonlinear unmixing technique for intimate mixtures using the
Hapke model and convolutional neural networks (HapkeCNN). We use the Hapke model …

Hyperspectral unmixing is a crucial task in hyperspectral image processing and analysis. It
aims to decompose mixed pixels into pure spectral signatures and their associated …

Since remote sensing images offer unique access to the distribution of land cover on earth,
many countries are investing in this technique to monitor urban sprawl. For this purpose, the …

Spectral pixels are often a mixture of the pure spectra of the materials, called endmembers,
due to the low spatial resolution of hyperspectral sensors, double scattering, and intimate …

Remote sensing-assisted monitoring of forest health entails methods that can provide up-to-
date and accurate information on decline and mortality of individual trees, while maintaining …

The subject of this thesis is blind hyperspectral unmixing using deep learning based
autoencoders. Two methods based on autoencoders are proposed and analyzed. Both …

This work discusses the problem of unsupervised classification in images. Conventional
methods approached this problem with the naive assumption that the relationship among …