Effect of Atmospheric Turbulence on the Performance of Underwater Wireless SAC-OCDMA System

Research on super-resolution reconstruction of remote sensing images: a comprehensive review

“…As distortions caused by clouds, atmospheric turbulence, and other noise sources often vary across regions in LR remote sensing images, local distortions should be considered, but conventional iterative back projection cannot handle individual local distortions. 33,34 Thus Li et al 35 improved iterative back projection by merging an inverse combination algorithm and a positive combination algorithm, improving elastic registration, and the image spatial resolution. Nevertheless, as iterative back projection is used for SR reconstruction of single-frame remote sensing images, the strong edges of the reconstructed image present the sawtooth effect.…”