RBM-based joint dictionary learning for ISAR resolution enhancement

RBM-based joint dictionary learning for ISAR resolution enhancement

In this study, an inverse synthetic aperture radar (ISAR) image resolution enhancement algorithm based on joint dictionary learning is proposed, by which two special sets of sparse signals called dictionaries are solved by exploiting numerous high-resolution (HR) and low-resolution (LR) ISAR images....

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Bibliographic Details
Main Authors: Jiaqi Ye, Dan Qin, Yifan Zhang, Xunzhang Gao
Format: Article
Language:English
Published: Wiley 2019-09-01
Series:The Journal of Engineering
Subjects:
boltzmann machines
learning (artificial intelligence)
image reconstruction
radar imaging
image enhancement
image resolution
dictionaries
synthetic aperture radar
image representation
radar signals
lr isar image shares
hr isar image
lr dictionary
hr dictionary
similar sparse representation coefficients
classical dictionary training algorithms
rbm-based joint dictionary
isar resolution enhancement
inverse synthetic aperture radar image resolution enhancement algorithm
joint dictionary learning
sparse signals
coupled dictionary learning algorithm
restricted boltzmann machine
image patches
similar scattering-centre models
Online Access:https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0732

Internet

https://digital-library.theiet.org/content/journals/10.1049/joe.2019.0732

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