Correlation estimation for remote sensing compressed-sensed video sampling

Compressed sensing (CS) is a new signal processing theory that provides an insight into signal processing. The CS theory has numerous potential applications in various fields, such as image processing, astronomical data analysis, analog-to-information, medical imaging, and remote sensing (RS) imager...

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Bibliographic Details
Published in:Journal of electronic imaging 2014-11, Vol.23 (6), p.063007-063007
Main Authors: Li, Sheng-liang, Liu, Kun, Zhang, Li, Wang, Jie, Zhang, Zhi-zhou, Han, Da-peng
Format: Article
Language:English
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Summary:Compressed sensing (CS) is a new signal processing theory that provides an insight into signal processing. The CS theory has numerous potential applications in various fields, such as image processing, astronomical data analysis, analog-to-information, medical imaging, and remote sensing (RS) imagery. The CS theory is applied to RS video imagery. An RS video based on a compressed sensing (RS-VCS) framework with correlation estimation measurement is proposed, along with a block measurement correlation model and corresponding reconstruction. The linearized Bregman algorithm is used to solve the reconstruction model, and the performance of the RS-VCS framework is simulated numerically.
ISSN:1017-9909
1560-229X
DOI:10.1117/1.JEI.23.6.063007