This paper reports on the results from ordinary least squares and ridge regression as statistical methods, and is compared to numerical optimization methods such as the stochastic method for global optimization, simulated annealing, particle swarm optimization and limited memory Broyden-Fletcher-Goldfard-Sharon bound optimization method. We used each of the above mentioned methods in estimating...

Unlike conventional sensor systems such as Landsat-TM, Spot-MX or IRS-LISS, which acquire data in only a few spectral bands, the development of scanner systems that acquire data in many narrow-wavelength bands allows the use of almost continuous reflectance data in studies of the Earth’s surface. This not only produces laboratory-like reflectance spectra with absorption bands specific to object...

In this work, we jointly process high spectral and high geometric resolution images and exploit their synergies to (a) generate a fused image of high spectral and geometric resolution; and (b) improve (linear) spectral unmixing of hyperspectral endmembers at subpixel level w.r.t. the pixel size of the hyperspectral image. We assume that the two images are radiometrically corrected and geometric...

Spectral unmixing techniques are widely used for hyperspectral data analysis and quantification. Many novel applications have been developed from the unmixing point of view, including surface constituent identification for land use mapping, disaster assessment, geology, biological process analysis and change detection (Keshava and Mustard, 2002). All existing unmixing approaches require a previ...

A snow-cover mapping method accounting for forests (SnowFrac) is presented. SnowFrac uses spectral unmixing and endmember constraints to estimate the snow-cover fraction of a pixel. The unmixing is based on a linear spectral mixture model, which includes endmembers for snow, coniferous trees, branches of leafless deciduous trees and snow-free ground. Model input consists of a land-cover fractio...

The analysis of hyperspectral images on the basis of the spectral decomposition of their pixels through the so called spectral unmixing process, has applications in tematic map generation, target detection and unsupervised image segmentation. The critical step is the determination of the endmembers used as the references for the unmixing process. We give a comprehensive enumeration of the metho...

Multispectral karyotyping analyzes all chromosomes in a single cell by labeling them with chromosome-specific probes conjugated to unique combinations of fluorophores. Currently available multispectral karyotyping systems require the purchase of specialized equipment and reagents. However, conventional laser scanning confocal microscopes that are capable of separating multiple overlapping emiss...