Abstract: A method of communicating data between at least two coprocessors in a single computing environment wherein one of the coprocessors is a transmitting processor and the other of the coprocessors is a receiving processor and the single computing environment includes a memory accessible by the coprocessors includes, among other things, determining in the transmitting processor the size of data to be communicated, attaching the data to a message and transmitting the message to the receiving processor if the size of the data is below or equal to a predetermined threshold value, and transmitting to the receiving processor a pointer that points to a location of the data in the memory if the size of the data is above the predetermined threshold value.

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 10 of modeling hyperspectral images includes building a scene in a first frame with objects and materials using a three dimensional modeling tool 16, selecting one or more hyperspectral bands and changing the reflectivity of each object and material 20 in the scene to correspond to reflectivity in the hyperspectral bands, changing the emissivity of a spectral source 24 for each object and material in the scene to correspond to the emissivity of the spectral source in the hyperspectral bands, rendering the scene to generate a hyperspectral image 28, and repeating the process for subsequent frames 30.

Abstract: The invention relates a method of identifying a tracked object that has a known database of hyperspectral and spatial information. The method associates an identifier with the tracked object; selects a parameter associated with the hyperspectral or spatial information of the tracked object; detects a deviation in the selected parameter; compares the deviation with the database; and if the deviation exceeds a predetermined threshold, assigns a new identifier to the tracked object, and if the deviation does not exceed the predetermined threshold, continues tracking the tracked object.

Abstract: A method for developing software in a parallel computing environment comprises the steps of developing a sequential implementation and parallel implementation of the software and verifying the results of the parallel implementation of the software against the results of the sequential implementation of the software.

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 multispectral staring array comprises, amongst other things, at least two sensors where each sensor is adapted to detect an image in a different predetermined spectral sensitivity; a first lens to focus capture spectral bands; a spectral filter between the lens and the sensors to subdivide the incident spectral bands; and a second lens to direct and focus the subdivided incident spectral bands on each of the sensors.

Abstract: The invention relates to a method of evaluating the confidence of matching signatures of a hyperspectral image of at least one tracked object, defined by pixels on an image sensor, to a hyperspectral image template in real time while tracking the at least one tracked object.

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 improving a spectral reflectance profile of an object using a hyperspectral imaging device includes, among other things, obtaining a series of hyperspectral images of the object where there is relative motion between the object and the hyperspectral imaging device; determining one or more parameters of the relative motion; mapping the parameters to determine an orientation of the object in each hyperspectral image in the series; identifying two or more spatial portions of the object in each hyperspectral image in the series; assigning a spectral signature to each spatial portion; and generating a multi-dimensional spectral reflectance profile from the orientation, the spatial portions, and the spectral signatures.

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 communicating data between at least two coprocessors in a single computing environment wherein one of the coprocessors is a transmitting processor and the other of the coprocessors is a receiving processor and the single computing environment includes a memory accessible by the coprocessors includes, among other things, determining in the transmitting processor the size of data to be communicated, attaching the data to a message and transmitting the message to the receiving processor if the size of the data is below or equal to a predetermined threshold value, and transmitting to the receiving processor a pointer that points to a location of the data in the memory if the size of the data is above the predetermined threshold value.

Abstract: Method of controlling the resolution of a hyperspectral image from an image sensor comprising pixels and at least one filter that defines subpixels within each pixel includes defining a window on the image sensor with an array of rows and columns of subpixels; weighting the subpixels within the window based upon one or more predefined parameters of the hyperspectral image to establish a value for a weighted average for the array for the predefined parameters; shifting the window by a predefined number of rows or columns; repeating the weighting and shifting steps for all possible windows on the image sensor; and processing the hyperspectral image based on the weighted averages.

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 removing stationary objects from hyperspectral imagery, includes among other things, collecting a series of hyperspectral images of a target scene; determining at least one first hyperspectral image having no moving or new objects in the target scene; selecting the at least one first hyperspectral image; determining at least one second hyperspectral image having moving objects in the target scene; and subtracting the at least one first hyperspectral image from the at least one second hyperspectral image to create a background-subtracted hyperspectral image.

Abstract: A multispectral staring array comprises, amongst other things, at least two sensors where each sensor is adapted to detect an image in a different predetermined spectral sensitivity; a first lens to focus capture spectral bands; a spectral filter between the lens and the sensors to subdivide the incident spectral bands; and a second lens to direct and focus the subdivided incident spectral bands on each of the sensors.

Abstract: A method 10 of modeling hyperspectral images includes building a scene in a first frame with objects and materials using a three dimensional modeling tool 16, selecting one or more hyperspectral bands and changing the reflectivity of each object and material 20 in the scene to correspond to reflectivity in the hyperspectral bands, changing the emissivity of a spectral source 24 for each object and material in the scene to correspond to the emissivity of the spectral source in the hyperspectral bands, rendering the scene to generate a hyperspectral image 28, and repeating the process for subsequent frames 30.

Abstract: Method of controlling the resolution of a hyperspectral image from an image sensor comprising pixels and at least one filter that defines subpixels within each pixel includes defining a window on the image sensor with an array of rows and columns of subpixels; weighting the subpixels within the window based upon one or more predefined parameters of the hyperspectral image to establish a value for a weighted average for the array for the predefined parameters; shifting the window by a predefined number of rows or columns; repeating the weighting and shifting steps for all possible windows on the image sensor; and processing the hyperspectral image based on the weighted averages.