Earth observing satellites usually not only take ordinary red-green-blue images, but provide several images including the near-infrared and infrared spectrum. These images are called multispectral, for about four to seven different bands, or hyperspectral, for higher dimensional images of up to 210 bands. The drawback of the additional spectral information… (More)
—The goal of pan-sharpening is to fuse a low spatial resolution multispectral image with a higher resolution panchro-matic image to obtain an image with high spectral and spatial resolution. The Intensity-Hue-Saturation (IHS) method is a popular pan-sharpening method used for its efficiency and high spatial resolution. However, the final image produced… (More)
Given discrete event data, we wish to produce a probability density that can model the relative probability of events occurring in a spatial region. Common methods of density estimation, such as Kernel Density Estimation, do not incorporate geographical information. Using these methods could result in non-negligible portions of the support of the density in… (More)
In this paper, we extend the Chan-Vese model for image segmentation in  to hyperspectral image segmentation with shape and signal priors. The use of the Split Bregman algorithm makes our method very efficient compared to other existing segmentation methods incorporating priors. We demonstrate our results on aerial hyperspectral images.
Recent research in perinatal pathology argues that analyzing properties of the placenta may reveal important information on how certain diseases progress. One important property is the structure of the placental blood vessels, which supply a fetus with all of its oxygen and nutrition. An essential step in the analysis of the vascular network pattern is the… (More)