18 November 2014 Correlation estimation for remote sensing compressed-sensed video sampling
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Abstract
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.
© 2014 SPIE and IS&T
Sheng-liang Li, Sheng-liang Li, Kun Liu, Kun Liu, Li Zhang, Li Zhang, Jie Wang, Jie Wang, Zhi-zhou Zhang, Zhi-zhou Zhang, Da-peng Han, Da-peng Han, } "Correlation estimation for remote sensing compressed-sensed video sampling," Journal of Electronic Imaging 23(6), 063007 (18 November 2014). https://doi.org/10.1117/1.JEI.23.6.063007 . Submission:
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