Sensing Matrix Design for Compressive Spectral Imaging via Binary Principal Component Analysis-Reference-Cited by-同舟云学术

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Sensing Matrix Design for Compressive Spectral Imaging via Binary Principal Component Analysis

Published:2020 Issue: Volume:29 Page:4003-4012
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Monsalve Jonathan^ORCID,Rueda-Chacon Hoover^ORCID,Arguello Henry

Funder

Colciencias/Department of Santander Scholarship

Postdoctoral Internship Program of the VIEUIS

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/8835130/08937037.pdf?arnumber=8937037

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Compressed Sensing-Based Data Acquisition via Intelligent Vehicles;IEEE Sensors Letters;2024-03

2. Covariance Estimation From Compressive Data Partitions Using a Projected Gradient-Based Algorithm;IEEE T IMAGE PROCESS;2022

3. Covariance Estimation From Compressive Data Partitions Using a Projected Gradient-Based Algorithm;IEEE Transactions on Image Processing;2022

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