A fast satellite image super-resolution technique using multicore processing

Abstract

Sparse representation based single image super-resolution technique requires several regularization problems to be solved to generate the desired output. It is computationally intensive and needs a considerable time if we implement sequentially on a single core processor. Remote sensing applications generally require high resolution satellite images on a near real-time instant. Since, satellite images are of larger dimensions, so obtaining desired high resolution images within some practical time will be highly data intensive. Therefore, fast super-resolution based post-processing may be integrated into the existing system either in software or hardware for practical applications. In this paper, we implement an OpenMP based parallel processing technique for single image super-resolution of multispectral satellite images. Results not only show a promising speed up in the execution time but provide visually enhanced outputs as well, compared to some of the existing methods.