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

In this paper, aiming to improve the spatial resolution of small satellite optical imaging, we propose a super-resolution (SR) algorithm based on rotation of 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 a super-resolution algorithm to reconstruct high-resolution images using the obtained data, which can significantly improve 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 proposed method has increased by 0.1607 (39%) and 1.88 times, respectively, compared to standard sampling. Additionally, 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 proposed method is improved by 0.24° and 0.05° compared to 45° and 26.56° oblique sampling, respectively.