A unified framework for damaged image fusion and completion based on low-rank and sparse decomposition

作者：

Highlights：

• We establish a unified framework for damaged image fusion and completion.

• We formulate a novel low-rank and sparse dictionary learning model.

• We develop an image decomposition and completion model for the damaged image.

摘要

•We establish a unified framework for damaged image fusion and completion.•We formulate a novel low-rank and sparse dictionary learning model.•We develop an image decomposition and completion model for the damaged image.

论文关键词：Image fusion,Image completion,Image decomposition,Low-rank and sparse representation,Dictionary learning

论文评审过程：Received 18 November 2020, Revised 12 June 2021, Accepted 21 July 2021, Available online 4 August 2021, Version of Record 12 August 2021.

论文官网地址：https://doi.org/10.1016/j.image.2021.116400