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...

This paper proposes a novel algorithm for the recovery of noisy bands from hyperspectral images. The method, based on spectral unmixing, relies on the spectral behavior of the materials on ground composing each image element. Firstly, reference spectra related to the classes of interest are used to perform spectral unmixing: these exhibit negligible noise influences as they are averaged over ar...

The urban environment is characterized by an intense use of the available space, where the preservation of open green spaces is of special ecological importance. Because of dynamic urban development and high mapping costs, municipal authorities are interested in effective methods for mapping urban surface cover types that can be used for evaluating ecological conditions in urban structures and ...

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...

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 ...

In the last years, hyperspectral analysis have been applied in many remote sensing applications. In fact, hyperspectral unmixing has been a challenging task in hyperspectral data exploitation. This process consists of three stages: (i) estimation of the number of pure spectral signatures or endmembers, (ii) automatic identification of the estimated endmembers, and (iii) estimation of the fracti...

In this paper, a new method is presented for spatial resolution enhancement of hyperspectral images (HSI) using spectral unmixing and a Bayesian sparse representation. The proposed method combines the high spectral resolution from the HSI with the high spatial resolution from a multispectral image (MSI) of the same scene and high resolution images from unrelated scenes. The fusion method is bas...

Magnetic paleoclimatic records often represent mixed environmental signals. Unmixing these signals may improve our understanding of the paleoenvironmental information contained within these records, but such a task is challenging. Here we report an example of numerical unmixing of magnetic hysteresis data obtained from Chinese loess and red clay sequences. We find that the mixed magnetic assemb...

and efficient solution to the unmixing problem. independence great discrimination ability on unlike signatures, giving a robust The model has great noise robustness, a correlation rate and endmember number always low Error Ratios for all cases. components, endmember number and proportion on the mixture, providing network behaviour vs. the Signal-to-Noise Ratio, correlation rate between order to...

The hyperspectral subpixel detection and classification problem has been intensely studied in the downward-looking case, typically satellite imagery of agricultural and urban areas. In contrast, the hyperspectral imaging case when "looking up" at small or distant satellites creates new and unforeseen problems. Usually one pixel or one fraction of a pixel contains the imaging target, and spectra...