The direct detection of exoplanets with high-contrast instruments can be boosted high spectral resolution. For integral field spectrographs yielding hyperspectral data, this means that the view consists diffracted starlight spectra and a spatially localized planet. Analysis usually relies on cross-correlation theoretical spectra. In purely blind-search context, supervised strategy biased model ...

Spectral unmixing is a consequential preprocessing task in hyperspectral image interpretation. With the help of large spectral libraries, equivalent to finding optimal subset library entries that can best model image. Sparse regression techniques have been widely used solve this optimization problem, since number materials present scene usually small. However, high mutual coherence signatures n...

The recent evolution of hyperspectral imaging technology and the proliferation new emerging applications presses for processing multiple temporal images. In this work, we propose a novel spectral unmixing (SU) strategy using physically motivated parametric endmember representations to account variability. By representing multitemporal mixing process state-space formulation, are able exploit Bay...

The objectives of this study are to evaluate the potential of Hyperspectral Mapper (HyMap) data and a spectral mixture model to characterize forest stands in a mixed coniferous and deciduous forest. A HyMap image was flown over a standard research site in Western Switzerland in summer 1998. The research forest-site can be characterized as heavily mixed forest. HyMap data were used to map the fo...

Nonlinear spectral mixture analysis (NSMA) is a widely used unmixing algorithm. It can fit the mixed spectra adequately, but collinearity effect among true and virtual endmembers will decrease the retrieval accuracies of endmember fractions. Use of linear spectral mixture analysis (LSMA) can effectively reduce the degree of collinearity in the NSMA. However, the inadequate modeling of mixed spe...

Spectral unmixing and sub-pixel mapping have been used to estimate the proportion and spatial distribution of the different land-cover classes in mixed pixels at a sub-pixel scale. In the past decades, several algorithms were proposed in both categories; however, these two techniques are generally regarded as independent procedures, with most sub-pixel mapping methods using abundance maps gener...