Single image super resolution using local smoothness and nonlocal self-similarity priors

作者：

Highlights：

• A reconstruction-based single image super resolution method is presented.

• Local smoothness and nonlocal self-similarity priors are incorporated in our model.

• The Split Bregman Iteration is imitated to solve the L1-regularized problem.

• The proposed method can achieve higher quality results.

摘要

•A reconstruction-based single image super resolution method is presented.•Local smoothness and nonlocal self-similarity priors are incorporated in our model.•The Split Bregman Iteration is imitated to solve the L1-regularized problem.•The proposed method can achieve higher quality results.

论文关键词：Single image super resolution,Reconstruction-based,Local smoothness,Nonlocal self-similarity,Split Bregman Iteration

论文评审过程：Received 30 June 2015, Revised 14 January 2016, Accepted 14 January 2016, Available online 22 January 2016, Version of Record 6 April 2016.

论文官网地址：https://doi.org/10.1016/j.image.2016.01.007