Optimal combining fusion on degraded compressed sensing image reconstruction

作者：

Highlights：

• Multi-channel image fusion from degraded compressed sensing measurements.

• Degradation includes both multiplicative (random scaling) and additive noise.

• Linear regression for set of optimal weight calculation and rONE-L1 reconstruction.

• Improvement in PSNR by 2±0.34 dB over the existing methods at 70% measurements.

摘要

Highlights•Multi-channel image fusion from degraded compressed sensing measurements.•Degradation includes both multiplicative (random scaling) and additive noise.•Linear regression for set of optimal weight calculation and rONE-L1 reconstruction.•Improvement in PSNR by 2±0.34 dB over the existing methods at 70% measurements.

论文关键词：Compressed sensing,Image fusion,Optimal weight,l1-minimization

论文评审过程：Received 29 June 2016, Revised 14 November 2016, Accepted 28 December 2016, Available online 30 December 2016, Version of Record 27 January 2017.

论文官网地址：https://doi.org/10.1016/j.image.2016.12.010