Position constraint based face image super-resolution by learning multiple local linear projections
作者：
Highlights：
• We propose to train multiple local linear projections under the position constraint.
• Patches of the same position are assumed to favor the same local mapping function.
• Sparse inner structure of LR patches is expected to be preserved by the HR ones.
• HR patch is directly generated using the corresponding local linear projection.
• State-of-the-art visual and quantitative results have been achieved.
摘要
•We propose to train multiple local linear projections under the position constraint.•Patches of the same position are assumed to favor the same local mapping function.•Sparse inner structure of LR patches is expected to be preserved by the HR ones.•HR patch is directly generated using the corresponding local linear projection.•State-of-the-art visual and quantitative results have been achieved.
论文关键词：Image super-resolution,Local linear projection,Face hallucination,Sparse representation,Sparsity preserving projection
论文评审过程：Received 20 June 2014, Revised 18 November 2014, Accepted 5 January 2015, Available online 12 January 2015.
论文官网地址：https://doi.org/10.1016/j.image.2015.01.002
