Single depth map super-resolution via joint non-local self-similarity modeling and local multi-directional gradient-guided regularization

作者：

Highlights：

• Single depth map super-resolution via joint local and non-local constraints.

• The multidirectional gradient-guided model is used to explore local information.

• The group-based sparse model is used to explore non-local information.

摘要

•Single depth map super-resolution via joint local and non-local constraints.•The multidirectional gradient-guided model is used to explore local information.•The group-based sparse model is used to explore non-local information.

论文关键词：Single depth map,Super-resolution,Non-local self-similarity,Local constraint,Multi-directional gradient-guided regularization

论文评审过程：Received 3 October 2020, Revised 9 April 2021, Accepted 4 May 2021, Available online 21 May 2021, Version of Record 8 June 2021.

论文官网地址：https://doi.org/10.1016/j.image.2021.116313