Medical image super-resolution with non-local embedding sparse representation and improved IBP

Medical image super-resolution with non-local embedding sparse representation and improved IBP

Zhang, Mingli and Desrosiers, Christian and Qu, Qiang and Guo, Fenghua and Zhang, Caiming

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing – Proceedings 2016

Abstract : This paper proposes a novel super-resolution method that exploits the sparse representation and non-local similarity of patches for the effective reconstruction of images. Highresolution images are reconstructed from low resolution observations with an efficient technique based on the alternating direction method of multipliers (ADMM). A robust iterative back-projection approach is used in a post-processing step to remove residual noise and artifacts in the reconstructed image. Experiments on benchmark medical images illustrate the advantage of our method, in terms of PSNR and SSIM, compared to state of the art approaches.