Mixed pixels are common in hyperspectral remote sensing images. Endmember extraction is a key step in spectral unmixing. The linear spectral mixture model (LSMM) constitutes a geometric approach that is commonly used for this purpose. This paper introduces the use of artificial bee colony (ABC) algorithms for spectral unmixing. First, the objective function of the external minimum volume model ...

expensive to provide these maps  with field measurements  therefore  it is better to use new methods. this study provides a lithological and alteration mapping units with dominant minerals based on hyperspectral images of eo1-hyperion satellite. to do so, two different zones  were  investigated:  the  cuprite-nevada  and  mozahem  volcano  in  iran  which  have suitable conditions for our study...

The advent of hyperspectral image technology is a major leap in recent years, it obtains the surface of the earth image contains rich space, radiation and spectral information, Mixed pixels not only effects identification and classification precision of object, but also greatly hinder the development of quantitative remote sensing, so effectively interpret mixed pixels is an important problem f...

Assessing and Enabling Independent Component Analysis as a Hyperspectral Unmixing Approach

Abstract: Hyperspectral unmixing aims to estimate a set of endmembers and corresponding abundances in pixels. Nonnegative matrix factorization (NMF) and its extensions with various constraints have been widely applied to hyperspectral unmixing. L1/2 and L2 regularizers can be added to NMF to enforce sparseness and evenness, respectively. In practice, a region in a hyperspectral image may posses...

The use of airborne hyperspectral remote sensing imagery for automated mapping of submerged aquatic vegetation (SAV) in the tidal Potomac River was investigated for near to real-time resource assessment and monitoring. Airborne hyperspectral imagery and field spectrometer measurements were obtained in October of 2000. A spectral library database containing selected ground-based and airborne sen...

CHRIS/Proba represents a new generation of hyperspectral-oriented data that provides different viewing angles of the same scene. This multi-angle acquisition, with 18 bands between 0.4-1 μm at five different angles, can substantially improve characterization of various land-cover types. However, with around 18m pixel size, the spatial resolution is still too coarse for many applications. To imp...