Abstract: An apparatus and method are disclosed for hyperspectral imaging of a scene along an imaging path, from a viewpoint which is arranged to move relative to the scene. The method comprises acquiring hyperspectral image data of a portion of the scene from the viewpoint, along a first viewing direction relative to the viewpoint and redirecting the viewing direction from the first viewing direction to a second viewing direction relative to the viewpoint, in dependence of the relative movement, to maintain a view of said portion of the scene as the viewpoint moves along a portion of the imaging path.

Abstract: A data processing method is disclosed for processing hyperspectral image data of a scene. The method comprises sequentially receiving portions of the data at a data buffer to form a data set comprising a predefined number of data portions and calculating a set of global statistical parameters and data correction factors using the data forming the data set. The method further comprises receiving a further data portion at the data buffer and simultaneously removing the earliest received data portion at the data buffer, from the data set, and subsequently calculating a set of local statistical parameters using the data of the further data portion. The method further comprises updating the set of global statistical parameters using the set of local statistical parameters and correcting the data of the data portion removed from the data set using the correction factors.

Abstract: A data processing method is disclosed for processing hyperspectral image data of a scene. The method comprises sequentially receiving portions of the data at a data buffer to form a data set comprising a predefined number of data portions and calculating a set of global statistical parameters and data correction factors using the data forming the data set. The method further comprises receiving a further data portion at the data buffer and simultaneously removing the earliest received data portion at the data buffer, from the data set, and subsequently calculating a set of local statistical parameters using the data of the further data portion. The method further comprises updating the set of global statistical parameters using the set of local statistical parameters and correcting the data of the data portion removed from the data set using the correction factors.

Abstract: A data processing method and system are disclosed for processing hyperspectral image data of a scene for locating targets within the scene. The method comprises receiving hyperspectral image data from a scene at a receiver, the receiver comprising a plurality of receiver elements, each element being arranged to receive hyperspectral image data from a portion of the scene. The method further comprises comparing the hyperspectral image data received at each element with hyperspectral image data corresponding to known targets and assigning each element with a target label in dependence upon the comparison between the hyperspectral image data received at the element with hyperspectral image data of the known targets. The method further comprises combining elements of the receiver having the same target label, and which are located within a predefined range of each other, to determine the location of the target within the scene.

Abstract: An apparatus and method are disclosed for hyperspectral imaging of a scene along an imaging path, from a viewpoint which is arranged to move relative to the scene. The method comprises acquiring hyperspectral image data of a portion of the scene from the viewpoint, along a first viewing direction relative to the viewpoint and redirecting the viewing direction from the first viewing direction to a second viewing direction relative to the viewpoint, in dependence of the relative movement, to maintain a view of said portion of the scene as the viewpoint moves along a portion of the imaging path.

Abstract: A system and method for hyperspectral image processing receives (202) partial hyperspectral image data representing a portion of a complete hyperspectral image. The method computes (204) estimated mean and covariance values for the partial hyperspectral image data, and executes (206) a hyperspectral image processing algorithm using the estimated mean and covariance values as estimates of global mean and covariance values for the complete hyperspectral image.