A GPU-based implementation on super-resolution reconstruction

Super-resolution reconstruction (SRR) proposes a fusion of several low-quality images into one higher quality result with better optical resolution. However, due to the vast amount of calculation of the SRR algorithm, its implementation is too slow. In this paper, we present a GPU-based parallel implementation on SRR algorithm. The compute unified device architecture (CUDA) is a programming approach for performing scientific calculations on a graphics processing unit (GPU) as a data-parallel computing device. The proposed GPU-based implementation using CUDA is up to approximately 200 times faster than the corresponding optimized CPU counterparts.