A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is
The super-resolution (SR) reconstruction of remote sensing images is a low-cost and efficient method to improve their resolution, and it is often used for further image analysis. To understand the development of SR reconstruction of remote sensing images and research hotspots and trends, we examined its history and reviewed existing methods categorized into traditional, learning-based, and deep-learning-based methods. To evaluate the reconstruction performance, we conducted experimentsdoi:10.1117/1.oe.60.10.100901 fatcat:44ssaq55ebfkrghyatvo5lbr2m