This paper presents a system that integrates biologically and geometrically inspired approaches to detecting objects from hyperspectral and/or multispectral (HS/MS), multiscale, multiplatform imagery. First, dimensionality reduction methods are studied and used for hyperspectral dimensionality reduction. Then, a biologically inspired method, SLEGION (Spatial Locally Excitatory Globally Inhibito...

Maximum likelihood supervised classifications with 1-m 128 band hyperspectral data accurately map in-stream habitats in the Lamar River, Wyoming with producer’s accuracies of 91% for pools, 87% for glides, 76% for riffles, and 85% for eddy drop zones. Coarser resolution 5-m hyperspectral data and 1-m simulated multiband imagery yield lower accuracies that are unacceptable for inventory and anal...

Person re-identification in a multi-camera environment is an important part of modern surveillance systems. Person reidentification from color images has been the focus of much active research, due to the numerous challenges posed with such analysis tasks, such as variations in illumination, pose and viewpoints. In this paper, we suggest that hyperspectral imagery has the potential to provide u...

Hyperspectral imagery is a new type of high-dimensional image data which is now used in many Earth-based and planetary exploration applications. Many efforts have been devoted to designing and developing compression algorithms for hyperspectral imagery. Unfortunately, most available approaches have largely overlooked the impact of mixed pixels and subpixel targets, which can be accurately model...

Hyperspectral imagery is playing more and more important role in many fields such as geology, agriculture, environment, military, atmosphere and so on. We need to register Hyperspectral imagery so that we can build coherent image cubes and get coherent spectrum of pixels. Our concern in this paper is the Fourier-Mellin Transform (FMT) for image registration process and its related techniques fo...

In this paper we provide a brief review of recent advances in computational methods for hyperspectral image analysis with emphasis in hybrid approaches. Hyperspectral imagery acquisition and hyperspectral analysis are growing elds. The analysis of hyperspectral images will have an increasing impact in several application areas, i.e., Earth observation, planetology, food industry, quality proces...

This project seeks to develop the technology to fuse high spatial resolution MultiSpectral Imagery (MSI) with lower spatial resolution, but higher spectral resolution, HyperSpectral Imagery (HSI) to provided enhanced target detection and battlespace characterization. It seeks to push beyond traditional PAN sharpening techniques to develop applications that will increase the accuracy and fidelit...

Invasive species’ phenologies often contrast with those of native species, representing opportunities for detection of invasive species with multi-temporal remote sensing. Detection is especially critical for ecosystem-transforming species that facilitate changes in disturbance regimes. The African C4 grass, Pennisetum ciliare, is transforming ecosystems on three continents and a number of neot...