Todd Wittman

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The goal of pan-sharpening is to fuse a low spatial resolution multispectral image with a higher resolution panchromatic 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)
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)
We discuss the problem of interpolating visually acceptable images at a higher resolution. We first present the interpolation problem and why linear interpolation filters are inadequate for image data. To represent the major mathematical approaches to image processing, we discuss and evaluate five different image interpolation methods. First, we present a(More)
In the past there has been little study to determine an optimal dimension reduction algorithm on hyperspectral images. In this paper we investigate the performance of different dimension reduction algorithms including PCA and Isomap using various hyperspectral tasks to compare them. We considered runtime, classification, anomaly dection, target detection(More)
Although hyperspectral images contain much more information than regular RGB images, more than ninety percent of the variance can be explained by a small portion of the data. The goal of dimension reduction is to map high dimensional data into a lower dimension while preserving the main features of the original data. The dimension reduction codes are taken(More)
Linear barcodes—the ubiquitous alternating black and white stripes whose relative widths encode information—are used in shipping, tracking, and identification and come in more than 250 varieties. The most familiar is probably the UPC barcode used in supermarkets; based on their grocery-shopping experience, most readers probably consider the reading of(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 nonnegligible portions of the support of the density in(More)