Abstract: In coded aperture imaging knowledge of the coded array pattern and its positional relation to the detector array is needed in order to be able to reconstruct the scene image. Usually a theoretical model of the coded array is used and the actual array needs to be aligned accurately with respect to the detector. The present invention uses a coded aperture imager to image a reference object in the scene and uses the intensity pattern on the detector array to determine the decoding pattern corresponding to the coded aperture array. The reference object may be a point source in which case the pattern on the detector array may be used directly as the decoding pattern or it may be used to correct a theoretical pattern for any misalignment.

Abstract: A method of classifying an object, in particular of classifying a vehicle by evaluating the degree of correlation between an image data set corresponding to an image of at least part of the vehicle and each of a plurality of reference data sets each of which corresponds to a reference image of a vehicle comprises the steps of establishing the vehicle's aspect and selecting the plurality of reference data sets from a larger group of such data sets on the basis of the vehicle's aspect. By selecting from the larger group only those reference data sets which correspond to the vehicle's aspect, faster classification is achieved for a given level of processing resources. Alternatively, for a given processing or classification rate, the level of processing resources may be reduced compared to the prior art.