Artificial intelligence (AI) plays a growing role in remote sensing (RS). Applications of AI,
particularly machine learning algorithms, range from initial image processing to high-level …

In Earth observation, multimodal data fusion is an intuitive strategy to break the limitation of
individual data. Complementary physical contents of data sources allow comprehensive and …

Endmember extraction (EE) plays an important role in the quantitative analysis of
hyperspectral images, as the main step in the decomposition of mixed pixels. At present …

Endmember extraction plays an indispensable role in hyperspectral image processing,
which is also an important step to decompose the mixed pixels in spectral unmixing. Most of …

Due to the characteristics of the spectrum integration, information redundancy, spectrum
mixing phenomenon and nonlinearity of the hyperspectral remote sensing images, it is a …

In recent years, the introduction of multiobjective evolutionary algorithms (MOEAs) into the
field of endmember extraction (EE) in hyperspectral unmixing has demonstrated a breadth of …

This paper presents a novel approach for spectral unmixing of remotely sensed
hyperspectral data. It exploits probabilistic latent topics in order to take advantage of the …

Endmember extraction (EE) is a significant task in hyperspectral unmixing. From a
multiobjective optimization perspective, this task is extremely challenging because …

The presence of shadows has always been a troublesome problem in image processing
and can also affect spectral unmixing with hyperspectral remote sensing images. Traditional …

A hybrid inversion approach based on the quantum-behaved particle swarm optimization
(QPSO) method is presented in this article to solve electromagnetic inverse problems …