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An infrared (IR) sub-imaging system is composed of an optical scanning device and a single IR detector, which provides the target location information to the servo system. Currently, further improvement of positioning accuracy and imaging quality in the traditional rosette scanning guidance mode is experiencing a bottleneck. The emergence of the compressed sensing (CS) technique provides a new solution for this problem as it can recover a high-resolution IR image including richer information with fewer sampling points. In this paper, the complementarity of the CS framework and IR rosette sub-imaging system was analyzed. A new method to improve the resolution of reconstructed IR images, multi-frame joint compressive imaging (MJCI), was proposed. The simulation results revealed the potential of the CS technique when applied to the IR sub-imaging system and demonstrated that the proposed method performed well for reconstruction.

Background: The construction of measurement matrix becomes a focus in compressed sensing (CS) theory. Although random matrices have been theoretically and practically shown to reconstruct signals, it is still necessary to study the more promising deterministic measurement matrix.

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