A wide range of methods for analysis of airborne-and satellite-derived imagery continues to
be proposed and assessed. In this paper, we review remote sensing implementations of …

This article introduces a review on implementations of various methods to perform cloud
detection and its related applications such as detection of cloud shadow, types of cloud and …

In this paper, the use of Independent Component (IC) Discriminant Analysis (ICDA) for
remote sensing classification is proposed. ICDA is a nonparametric method for discriminant …

In the last few years the scientific community has realized that obtaining a better
understanding of interactions between natural systems and the man-made environment …

Hyperspectral data acquired from field-based platforms present new challenges for their
analysis, particularly for complex vertical surfaces exposed to large changes in the geometry …

Nonnegative matrix factorization (NMF) is a widely used method for blind spectral unmixing
(SU), which aims at obtaining the endmembers and corresponding fractional abundances …

Gaussian processes (GPs) represent a powerful and interesting theoretical framework for
Bayesian classification. Despite having gained prominence in recent years, they remain an …

Spectral mixture analysis has been an important research topic in remote sensing
applications, particularly for hyperspectral remote sensing data processing. On the basis of …

Because of recent advances of hyperspectral imaging technology with hundreds of spectral
bands being used for data acquisition, how to handle enormous data volumes using …

This paper considers the problem of unsupervised spectral unmixing for hyperspectral
image analysis. Each observed pixel is assumed to be a noisy linear mixture of pure …