Using sub-resolution features for selfcompensation of the modulation transfer function in remote sensing

Space smart optical orbiting payloads integrated with attitude and position (SSPIAP) are emerging as an essential tool that is extensively used in microsatellites. The onorbit imaging link of SSPIAPs includes atmospheric disturbances, defocusing, and relative motion, and other noises, thereby resulting in low modulation transfer function (MTF) and poor image quality. The introduction of MTF compensations has pushed the limits of optical imaging, enabling high-resolution on-orbit dynamic imaging. However, the external targets for compensating MTF are limited by space and time because the availability and access to external targets are infrequently easy when a remote sensor is working on-orbit. Here, a new and robust MTF self-compensation method for a SSPIAP is proposed. In comparison with conventional methods with external targets, this method utilizes multiple natural subresolution features (SRFs), occupying several pixels on a uniform background, as observation targets which makes MTFC more maneuverable, robust and authentic. A mathematical morphology algorithm is used to extract SRFs. Moreover, the method relies on a regularization total variation energy function, a sparse prior framework, to invert the MTF. Experimental measurements confirm that the proposed method is effective and convenient to implement. This technique does not rely on specific external targets to compensate the MTF, making it potentially suitable for on-orbit dynamic long-range imaging.