A simple framework to leverage state-of-the-art single-image super-resolution methods to restore light fields

作者：

Highlights：

• The proposed method is a simple framework that extends single image super-resolution for light field super-resolution.

• This is achieved by compacting the energy of the light field and apply single image super-resolution on the principal basis.

• Experimental results show that the proposed method is competitive to recent light field super-resolution methods.

• Moreover, the proposed method achieve better subjective results even when consider non-Lambertian surfaces.

摘要

•The proposed method is a simple framework that extends single image super-resolution for light field super-resolution.•This is achieved by compacting the energy of the light field and apply single image super-resolution on the principal basis.•Experimental results show that the proposed method is competitive to recent light field super-resolution methods.•Moreover, the proposed method achieve better subjective results even when consider non-Lambertian surfaces.

论文关键词：Light fields,Super-resolution,Convolutional neural networks,Single image super resolution

论文评审过程：Received 10 June 2019, Revised 11 September 2019, Accepted 11 September 2019, Available online 25 September 2019, Version of Record 16 October 2019.

论文官网地址：https://doi.org/10.1016/j.image.2019.115638