2016/12/08 by Ruben Fernandez-Beltran, Rubén Fernández-Beltrán, Pedro Latorre-Carmona +2 · 1 citation
Computer Science · Physics and Astronomy · #Advanced Image Processing Techniques #Adaptive optics and wavefront sensing #Advanced Vision and Imaging
paper · doi:10.1080/01431161.2016.1264027
Image acquisition technology is improving very fast from a performance point of view. However, there are physical restrictions that can only be solved using software processing strategies. This is particularly true in the case of super resolution (SR) methodologies. SR techniques have found a fertile application field in airborne and space optical acquisition platforms. Single-frame SR methods may be advantageous for some remote-sensing platforms and acquisition time conditions. The contributions of this article are basically two: (1) to present an overview of single-frame SR methods, making a comparative analysis of their performance in different and challenging remote-sensing scenarios, and (2) to propose a new single-frame SR taxonomy, and a common validation strategy. Finally, we should emphasize that, on the one hand, this is the first time, to the best of our knowledge, that such a review and analysis of single SR methods is made in the framework of remote sensing, and, on the other hand, that the new single-frame SR taxonomy is aimed at shedding some light when classifying some types of single-frame SR methods.