Imaging spectroscopy, also known as hyperspectral imaging, is a new technique that has gained tremendous popularity in many research areas, including satellite imaging and aerial reconnaissance. In particular, NASA is continuously gathering high-dimensional image data from the surface of the earthwith hyperspectral sensors such as the Jet Propulsion Laboratory’s Airborne Visible-Infrared Imagin...

This paper gives a brief survey of remote sensing techniques from a viewpoint of pattern recongition and media understanding (PRMU). First we give a brief summary of remote sensing, and then introduce related work on both remote sensing image processing and some unique issues in remote sensing image processing. We moreover point out that the future direction of remote sensing is expected to be ...

Endmember extraction and spectral unmixing is a very challenging task in multispectral/hyperspectral image processing due to the incompleteness of information. In this paper, a new method for endmember extraction and spectral unmixing of hyperspectral images is proposed, which is called as minimum distance constrained nonnegative matrix factorization (MDC-NMF). After being compared with a newly...

Hyperspectral remote sensing images provide richer information about materials than that of multispectral images. The new larger data volumes of hyperspectral sensors bring new challenges for traditional image processing techniques. Therefore, conventional classification methods could fail without employing dimension reduction preprocessing. The dimensional reduction methods can be totally divi...

This paper investigates the efficiency of spectral screening as a tool for speedup in hyperspectral image processing. Spectral screening is a technique for reducing the hyperspectral data to a representative subset of spectra. The subset is formed such that any two spectra in it are dissimilar and, for any spectrum in the original image cube, there is a similar spectrum in the subset. The simil...

Hyperspectral image processing algorithms are computationally very costly, which makes them good candidates for parallel and, specifically, GPU processing. Extreme Learning Machine (ELM) is a recently proposed classification algorithm very suitable for its implementation on GPU platforms. In this paper we propose an efficient GPU implementation of an ELM-based classification strategy for hypers...

The emerging astronomical technique known as wide-field spatiospectral interferometry can provide hyperspectral images with spatial resolutions that are unattainable with a single monolithic-aperture observatory. The theoretical groundwork for operation and data measurement is presented in full detail, including relevant coherence theory. We also discuss a data processing technique for recoveri...