Isotropic and anisotropic filtering norm-minimization: A generalization of the TV and TGV minimizations using NESTA

作者：

Highlights：

• A method for Compressive Sensing reconstruction of non-sparse signals was proposed.

• The method generalizes the TV and allows to reconstruct filtered sparse MRI images.

• We also implemented the isotropic and anisotropic models, modifying NESTA.

• Specific filter sets improve the reconstruction of specific types of images.

• Specific filter sets improve quality of MRI images when compared to NESTA TV.

摘要

•A method for Compressive Sensing reconstruction of non-sparse signals was proposed.•The method generalizes the TV and allows to reconstruct filtered sparse MRI images.•We also implemented the isotropic and anisotropic models, modifying NESTA.•Specific filter sets improve the reconstruction of specific types of images.•Specific filter sets improve quality of MRI images when compared to NESTA TV.

论文关键词：Compressive sensing,Filtering,NESTA,MRI

论文评审过程：Received 12 June 2019, Revised 19 February 2020, Accepted 12 April 2020, Available online 18 April 2020, Version of Record 30 April 2020.

论文官网地址：https://doi.org/10.1016/j.image.2020.115856