Abstract: A method of tracking motion of at least one object of a group of moving objects using hyperspectral imaging includes, among other things, obtaining a series of hyperspectral image frames; comparing each frame in the series to a template to determine changes in the image between frames; identifying a group of pixels in each frame associated with the changes; identifying changes as motion of the moving objects; correlating the pixel groups frame to frame to spatially determine at least one parameter of the motion of the objects; and correlating the pixel groups with a spectral reflectance profile associated with the at least one object wherein the track of the at least one object is distinguishable from the tracks of other moving objects.

Abstract: A method of referencing an imaged object includes, among other things, obtaining a series of images, observing key characteristics of the object in each of the series of images, associating the observed key characteristics with the object; and assigning a unique identifier to the object based upon the associated key characteristics. The series of images includes spectral and spatial imagery. Some of the key characteristics are in the spectral imagery and some of the key characteristics are in the spatial imagery.

Abstract: A method of referencing an imaged object includes, among other things, obtaining a series of images, observing key characteristics of the object in each of the series of images, associating the observed key characteristics with the object; and assigning a unique identifier to the object based upon the associated key characteristics. The series of images includes spectral and spatial imagery. Some of the key characteristics are in the spectral imagery and some of the key characteristics are in the spatial imagery.

Abstract: The invention relates to a method of selecting an algorithm for use in processing hyperspectral data from a set of algorithms, each having qualities for processing certain characteristics of hyperspectral data.

Abstract: A method of removing a hyperspectral signature from at least one hyperspectral image, includes among other things, selecting a hyperspectral signature and determining a dissimilarity value between each pixel in the at least one hyperspectral image and the selected at least one hyperspectral signature. If the dissimilarity value between the signature of a given pixel in the at least one hyperspectral image and the selected at least one hyperspectral signature is less than a predetermined threshold value then the value of the signature for the given pixel is set to zero to create a signature-subtracted hyperspectral image.

Abstract: A method of tracking motion of at least one object of a group of moving objects using hyperspectral imaging includes, among other things, obtaining a series of hyperspectral image frames; comparing each frame in the series to a template to determine changes in the image between frames; identifying a group of pixels in each frame associated with the changes; identifying changes as motion of the moving objects; correlating the pixel groups frame to frame to spatially determine at least one parameter of the motion of the objects; and correlating the pixel groups with a spectral reflectance profile associated with the at least one object wherein the track of the at least one object is distinguishable from the tracks of other moving objects.

Abstract: A method of removing a hyperspectral signature from at least one hyperspectral image, includes among other things, selecting a hyperspectral signature and determining a dissimilarity value between each pixel in the at least one hyperspectral image and the selected at least one hyperspectral signature. If the dissimilarity value between the signature of a given pixel in the at least one hyperspectral image and the selected at least one hyperspectral signature is less than a predetermined threshold value then the value of the signature for the given pixel is set to zero to create a signature-subtracted hyperspectral image.

Abstract: The invention relates to a method of selecting an algorithm for use in processing hyperspectral data from a set of algorithms, each having qualities for processing certain characteristics of hyperspectral data.