Improving the Spatial Resolution of Small Satellites by Implementing a Super-Resolution Algorithm Based on the Optical Imaging Sensor’s Rotation Approach

In this article, aiming to improve the spatial resolution of small satellite optical imaging, we propose a super-resolution (SR) algorithm based on the rotation of charge-coupled device (CCD) sensor sampler. The proposed method can effectively increase sampling density in both satellite’s flight direction and vertical direction to obtain images with a higher overlap ratio, thus acquiring more information than conventional optical satellites. We have proposed an SR algorithm to reconstruct high-resolution (HR) images using the obtained data, which can significantly improve the spatial resolution of remote-sensing satellite images. In addition, a method for quantitative evaluation of image quality improvement based on the modulation transfer function (MTF) is proposed. It is shown that the MTF value at a given spatial frequency and Nyquist frequency of the proposed method has increased by 0.1607 (39%) and 1.88 times, respectively, compared to standard sampling. In addition, sampling frequency of the proposed method has improved by 1.34 and 1.06 times compared to 45° and 26.56° oblique sampling, respectively. Also, the field of view (FOV) of imaging system of the proposed method is improved by 0.24° and 0.05° compared to 45° and 26.56° oblique sampling, respectively.