SGCRSR: Sequential gradient constrained regression for single image super-resolution

作者：

Highlights：

•

• A sequential gradient constrained regression-based image super-resolution method is proposed.

• A way to combine reconstruction-based and learning-based super-resolution methods is presented.

• Extensive experimental results demonstrate the effectiveness of the proposed framework.

摘要

•A sequential gradient constrained regression-based image super-resolution method is proposed.•A way to combine reconstruction-based and learning-based super-resolution methods is presented.•Extensive experimental results demonstrate the effectiveness of the proposed framework.

论文关键词：Image super-resolution,Sequential regression,Gradient constraint,Combination

论文评审过程：Received 1 December 2017, Revised 23 April 2018, Accepted 24 April 2018, Available online 2 May 2018, Version of Record 7 May 2018.

论文官网地址：https://doi.org/10.1016/j.image.2018.04.012