Results 11 to 20 of about 20,927 (220)

Microwave Sparse Imaging Applied to Stroke Monitoring

2021 XXXIVth General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS), 2021
We study the application of differential microwave sparse imaging in brain diagnostics. In particular, we describe the estimation stroke change between the consecutive measurements using l1 regularization. The method is verified using a realistic anthropomorphic human phantom.
Stevanovic, Marija Nikolic, Singh, Tushar, Ninkovic, Branislav, Kolundzija, Branko   +3 more
openaire   +1 more source

Sparse reconstruction algorithms for nonlinear microwave imaging [PDF]

2017 25th European Signal Processing Conference (EUSIPCO), 2017
Publication in the conference proceedings of EUSIPCO, Kos island, Greece ...
Zaimaga, Hidayet, Fraysse, Aurélia, Lambert, Marc   +2 more
openaire   +2 more sources

SAR Change Imaging in the Sparse Transforming Domain Based on Compressed Sensing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Since compressed sensing (CS) theory broke through the limitation of the traditional Nyquist sampling theory, it has attracted extensive attention in the field of microwave imaging.
Wenjiao Chen, Jiwen Geng, Ze Yu, Yukun Guo   +3 more
doaj   +1 more source

Verification of Complex Image Based Sparse SAR Imaging Method on GaoFen-3 Dataset

Leida xuebao, 2020
Sparse signal processing-based Synthetic Aperture Radar (SAR) imaging, also known as sparse SAR imaging, is the main research direction of sparse microwave imaging theory.
BI Hui, ZHANG Bingchen, HONG Wen, WU Yirong   +3 more
doaj   +1 more source

CSR-Net: A Novel Complex-Valued Network for Fast and Precise 3-D Microwave Sparse Reconstruction

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
Since the compressed sensing (CS) theory broke through the limitation of the traditional Nyquist sampling theory, it has attracted extensive attention in the field of microwave imaging.
Mou Wang, Shunjun Wei, Jun Shi, Yue Wu, Qizhe Qu, Yuanyuan Zhou, Xiangfeng Zeng, Bokun Tian   +7 more
doaj   +1 more source

Accelerated Sparse Microwave Imaging Phase Error Compensation Algorithm Based on Combination of SAR Raw Data Simulator and Map-drift Autofocus Algorithm

Leida xuebao, 2016
Sparse microwave imaging is new concept, theory and methodology of microwave imaging, which introduces the sparse signal processing theory to microwave imaging and combines them together to overcome the paradox of increasing system complexity and imaging
Zhang Zhe, Zhang Bingchen, Hong Wen, Wu Yirong   +3 more
doaj   +1 more source

Multiple feature-enhanced synthetic aperture radar imaging [PDF]

, 2009
Non-quadratic regularization based image formation is a recently proposed framework for feature-enhanced radar imaging. Specific image formation techniques in this framework have so far focused on enhancing one type of feature, such as strong point ...
Cetin, Mujdat, Masnadi-Shirazi, Mohammad Ali, Samadi, Sadegh, Çetin, Müjdat   +3 more
core   +1 more source

HPHR-SAR-Net: Hyperpixel High-Resolution SAR Imaging Network Based on Nonlocal Total Variation

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
High resolution is a key trend in the development of synthetic aperture radar (SAR), which enables the capture of fine details and accurate representation of backscattering properties.
Guoru Zhou, Zhongqiu Xu, Yizhe Fan, Zhe Zhang, Xiaolan Qiu, Bingchen Zhang, Kun Fu, Yirong Wu   +7 more
doaj   +1 more source

Parallel preconditioners for high order discretizations arising from full system modeling for brain microwave imaging [PDF]

, 2016
This paper combines the use of high order finite element methods with parallel preconditioners of domain decomposition type for solving electromagnetic problems arising from brain microwave imaging.
Bonazzoli, Cai, Dolean, Dolean, Hecht, Mikael, Nédélec, Parks, Rapetti, Rapetti, Semenov   +10 more
core   +5 more sources

L-Hypersurface Based Parameters Selection in Composite Regularization Models With Application to SAR and TomoSAR Imaging

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
Composite regularization models are widely used in sparse signal processing, making multiple regularization parameters selection a significant problem to be solved.
Yizhe Fan, Kun Wang, Jie Li, Guoru Zhou, Bingchen Zhang, Yirong Wu   +5 more
doaj   +1 more source