Infrared Image Registration and High-Resolution Reconstruction Using Multiple Translationally Shifted Aliased Video Frames

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IEEE Transactions on Instrumentation and Measurement


Forward looking infrared (FLIR) detector arrays generally produce spatially undersampled images because the FLIR arrays cannot be made dense enough to yield a sufficiently high spatial sampling frequency. Multi-frame techniques, such as microscanning, are an effective means of reducing aliasing and increasing resolution in images produced by staring imaging systems. These techniques involve interlacing a set of image frames that have been shifted with respect to each other during acquisition. The FLIR system is mounted on a moving platform, such as an aircraft, and the vibrations associated with the platform are used to generate the shifts. Since a fixed number of image frames is required, and the shifts are random, the acquired frames will not fall on a uniformly spaced grid. Furthermore, some of the acquired frames may have almost similar shifts thus making them unusable for high-resolution image reconstruction. In this paper, we utilize a gradient-based registration algorithm to estimate the shifts between the acquired frames and then use a weighted nearest-neighbor approach for placing the frames onto a uniform grid to form a final high-resolution image. Blurring by the detector and optics of the imaging system limits the increase in image resolution when microscanning is attempted at sub-pixel movements of less than half the detector width. We resolve this difficulty by the application of the Wiener filter, designed using the modulation transfer function (MTF) of the imaging system, to the high-resolution image. Simulation and experimental results are presented to verify the effectiveness of the proposed technique. The techniques proposed herein are significantly faster than alternate techniques, and are found to be especially suitable for real-time applications.

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IEEE: Institute of Electrical and Electronics Engineers



Peer Reviewed