Structured Low-Rank and Sparse Method for ISAR Imaging With 2-D Compressive Sampling
Author:
Affiliation:
1. State Key Laboratory of Millimeter Waves, School of Information Science and Engineering, Southeast University, Nanjing, China
2. Shanghai Academy of Space Technology, Shanghai, China
Funder
National Science Foundation of China
Natural Science Foundation of Jiangsu Province
ZhiShan Scholar Program of Southeast University
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/9633014/09950277.pdf?arnumber=9950277
Reference29 articles.
1. Unsupervised Recurrent Hyperspectral Imagery Super-Resolution Using Pixel-Aware Refinement
2. Enhancing ISAR Image Efficiently via Convolutional Reweighted l 1 Minimization
3. High-Resolution Inverse Synthetic Aperture Radar Imaging and Scaling With Sparse Aperture
4. Sparse Regularization of Interferometric Phase and Amplitude for InSAR Image Formation Based on Bayesian Representation
5. Removal of Micro-Doppler Effect of ISAR Image Based on Laplacian Regularized Nonconvex Low-Rank Representation
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