Video compressive sensing reconstruction via reweighted residual sparsity
The compressive sensing (CS) theory indicates that robust reconstruction of signals can be
obtained from far fewer measurements than those required by the Nyquist–Shannon …
obtained from far fewer measurements than those required by the Nyquist–Shannon …
Real time end-to-end learning system for a high frame rate video compressive sensing network
(57) ABSTRACT A real time end-to-end learning system for a high frame rate video
compressive sensing network is described. The slow reconstruction speed of conventional …
compressive sensing network is described. The slow reconstruction speed of conventional …
Enhanced deep-learning-based magnetic resonance image reconstruction by leveraging prior subject-specific brain imaging: Proof-of-concept using a cohort of …
Deep learning models have shown potential for reconstructing undersampled, multi-channel
magnetic resonance (MR) image acquisitions. Recently proposed methods, however, have …
magnetic resonance (MR) image acquisitions. Recently proposed methods, however, have …
Incorporating reference guided priors into calibrationless parallel imaging reconstruction
Purpose To propose and evaluate a new calibrationless parallel imaging method aimed at
further improving the reconstruction accuracy of the accelerated multi-channel MR images …
further improving the reconstruction accuracy of the accelerated multi-channel MR images …
Tree structure sparsity pattern guided convex optimization for compressive sensing of large-scale images
WJ Liang, GX Lin, CS Lu - IEEE Transactions on Image …, 2016 - ieeexplore.ieee.org
Cost-efficient compressive sensing of large-scale images with quickly reconstructed high-
quality results is very challenging. In this paper, we present an algorithm to solve convex …
quality results is very challenging. In this paper, we present an algorithm to solve convex …
Measurement structures of image compressive sensing for green internet of things (IoT)
R Li, X Duan, Y Li - Sensors, 2018 - mdpi.com
Image compressive sensing (CS) is a potential imaging scheme for green internet of things
(IoT). To further make CS-based sensor adaptable to low bandwidth and low power, this …
(IoT). To further make CS-based sensor adaptable to low bandwidth and low power, this …
Feature Adaptation Predictive Coding for Quantized Block Compressive Sensing of COVID-19 X-Ray Images
H Zheng, H Liu, G Chen - International Forum on Digital TV and Wireless …, 2022 - Springer
With the development of remote X-ray detection for Corona Virus Disease 2019 (COVID-19),
the quantized block compressive sensing technology plays an important role when remotely …
the quantized block compressive sensing technology plays an important role when remotely …
[PDF][PDF] Deep-learning-based Multi-visit Magnetic Resonance Imaging Reconstruction: Proof of Concept and Robustness Evaluation on a Cohort of Glioblastoma …
Y Beauferris - 2023 - prism.ucalgary.ca
Magnetic Resonance (MR) imaging is a powerful imaging technique for assessing brain-
related diseases. However, MR scans suffer from long acquisition times and as a …
related diseases. However, MR scans suffer from long acquisition times and as a …
[PDF][PDF] 高光谱摆扫型压缩成像及数据重建
贾应彪， 冯燕 - 红外技术, 2017 - hwjs.nvir.cn
高分辨率的应用需求使得传统的高光谱遥感成像系统面临高速率采样, 海量数据存储等难以突破
的瓶颈问题, 压缩感知理论为传统高光谱遥感所面临的瓶颈问题提供了解决可能 …
的瓶颈问题, 压缩感知理论为传统高光谱遥感所面临的瓶颈问题提供了解决可能 …
Feasibility of Laser Communication Beacon Light Compressed Sensing
Z Wang, S Gao, L Sheng - Sensors, 2020 - mdpi.com
The Compressed Sensing (CS) camera can compress images in real time without
consuming computing resources. Applying CS theory in the Laser Communication (LC) …
consuming computing resources. Applying CS theory in the Laser Communication (LC) …