Reference data (“ground truth”) maps have traditionally been used to assess the accuracy of classification algorithms. These maps typically classify pixels or areas of imagery as belonging to a finite number of ground cover classes, but do not include sub-pixel abundance estimates; therefore, they are not sufficiently detailed to directly assess the performance of spectral unmixing algorithms. ...

We investigated the area to the northwest of the Isidis impact basin (hereby referred to as “NW Isidis”) using thermal infrared emission datasets to characterize and quantify bulk surface mineralogy throughout this region. This area is home to Jezero crater and the watershed associated with its two deltaic deposits in addition to NE Syrtis and the strong and diverse visible/near-infrared spectr...

This paper presents a study about the potential of spectral unmixing of hyperspectral satellite image data for targeting and quantification of mineral content in limestone and bauxite rich areas in southern India. ASTER image (acquired in the VNIR and SWIR regions) has been used in conjunction with SRTM – DEM and field studies. A new approach of spectral unmixing of ASTER image data delineated ...

This paper presents a fast spectral unmixing algorithm based on Dykstra’s alternating projection. The proposed algorithm formulates the fully constrained least squares optimization problem associated with the spectral unmixing task as an unconstrained regression problem followed by a projection onto the intersection of several closed convex sets. This projection is achieved by iteratively proje...

In the North of Tunisia, Hammam Zriba region represents an important mine activity zone, it is among the most important in the Maghreb . The mine tailings cause the environment degradation, so it had polluted the atmosphere, the soils, the vegetation, the water quality and the ecosystem of the Hammam ouady (Dry River) which is discharged directly in the Miliane River. The Miliane River represen...

Remote sensing image analysis can be carried out at the per-pixel (hard) and sub-pixel (soft) scales. The former refers to the purity of image pixels, while the latter refers to the mixed spectra resulting from all objects composing of the image pixels. The spectral unmixing methods have been developed to decompose mixed spectra. Data-driven unmixing algorithms utilize the reference data called...

This paper examines the potential of ASTER data in mapping the geology of an arid area in Africa using spectral analysis techniques. Equipped with a relatively broad spectral range, fine spatial resolution, and a large number of bands, ASTER data are especially attractive to many geological researchers in Africa, due to their open availability and associated minimal costs for academic use. The ...

of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy HYPERSPECTRAL ENDMEMBER DETECTION AND BAND SELECTION USING BAYESIAN METHODS By Alina Zare December 2008 Chair: Paul Gader Major: Computer Engineering Four methods of endmember detection and spectral unmixing are described. The methods de...

BACKGROUND Currently, there are limited means for high-resolution monitoring of tissue injury during radiofrequency ablation procedures. OBJECTIVE To develop the next generation of visualization catheters that can reveal irreversible atrial muscle damage caused by ablation and identify viability gaps between the lesions. METHODS Radiofrequency lesions were placed on the endocardial surfaces...

Hyperspectral remote sensing allows for the detailed analysis of the surface of the Earth by providing high-dimensional images with hundreds of spectral bands. Hyperspectral image classification plays a significant role in hyperspectral image analysis and has been a very active research area in the last few years. In the context of hyperspectral image classification, supervised techniques (whic...