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

Mingli Zhang; Christian Desrosiers; Qiang Qu; Fenghua Guo; Caiming Zhang

ICASSP 2016accepted0 citations

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

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

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.

BibTeX

@inproceedings{icassp2016_medicalimagesupe,
  title = {Medical image super-resolution with non-local embedding sparse representation and improved IBP},
  author = {Mingli Zhang and Christian Desrosiers and Qiang Qu and Fenghua Guo and Caiming Zhang},
  booktitle = {ICASSP 2016},
  year = {2016}
}