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Compressed Sensing for Biomedical Photoacoustic Imaging: A Review [PDF]

Sensors
Photoacoustic imaging (PAI) is a rapidly developing emerging non-invasive biomedical imaging technique that combines the strong contrast from optical absorption imaging and the high resolution from acoustic imaging.
Yuanmao Wang, Yang Chen, Yongjian Zhao, Siyu Liu   +3 more
doaj   +2 more sources

Single-Shot Compressed Imaging via Random Phase Modulation

Applied Sciences, 2022
Compressed sensing (CS) provides an innovative framework for signal sampling, which enables accurate recovery of the sparse or compressible signal from a small set of linear measurements far fewer than the Nyquist rate in traditional signal processing ...
Cheng Zhang, Ru Zhang, Yuanyuan Zhu, Hairong Yang, Chuan Shen, Sui Wei   +5 more
doaj   +1 more source

Distributed Compressed Sensing of Hyperspectral Images According to Spectral Library Matching

IEEE Access, 2021
The ever-increasing resolution puts tremendous pressure to the onboard hyperspectral imaging system. Compressed sensing technology is one of the important ways to solve this problem.
Hua Xiao, Zhongliang Wang, Xueying Cui
doaj   +1 more source

Fully Learnable Model for Task-Driven Image Compressed Sensing

Sensors, 2021
This study primarily investigates image sensing at low sampling rates with convolutional neural networks (CNN) for specific applications. To improve the image acquisition efficiency in energy-limited systems, this study, inspired by compressed sensing ...
Bowen Zheng, Jianping Zhang, Guiling Sun, Xiangnan Ren   +3 more
doaj   +1 more source

An Image Compression Encryption Algorithm Based on Chaos and ZUC Stream Cipher

Entropy, 2022
In order to improve the transmission efficiency and security of image encryption, we combined a ZUC stream cipher and chaotic compressed sensing to perform image encryption.
Xiaomeng Song, Mengna Shi, Yanqi Zhou, Erfu Wang   +3 more
doaj   +1 more source

Distributed Compressed Hyperspectral Sensing Imaging Based on Spectral Unmixing

Sensors, 2020
The huge volume of hyperspectral imagery demands enormous computational resources, storage memory, and bandwidth between the sensor and the ground stations.
Zhongliang Wang, Hua Xiao
doaj   +1 more source

Wireless Transmission Method for Large Data Based on Hierarchical Compressed Sensing and Sparse Decomposition

Sensors, 2020
With the widespread application of wireless sensor networks, large-scale systems with high sampling rates are becoming more and more common. The amount of original data generated by the wireless sensor network is very large, and transmitting all the ...
Youtian Qie, Chuangbo Hao, Ping Song
doaj   +1 more source

A Task-Driven Invertible Projection Matrix Learning Algorithm for Hyperspectral Compressed Sensing

Remote Sensing, 2021
The high complexity of the reconstruction algorithm is the main bottleneck of the hyperspectral image (HSI) compression technology based on compressed sensing.
Shaofei Dai, Wenbo Liu, Zhengyi Wang, Kaiyu Li   +3 more
doaj   +1 more source

An Efficient Deep Learning-Based High-Definition Image Compressed Sensing Framework for Large-Scene Construction Site Monitoring

Sensors, 2023
High-definition images covering entire large-scene construction sites are increasingly used for monitoring management. However, the transmission of high-definition images is a huge challenge for construction sites with harsh network conditions and scarce
Tuocheng Zeng, Jiajun Wang, Xiaoling Wang, Yunuo Zhang, Bingyu Ren   +4 more
doaj   +1 more source

Deep Compressed Sensing Generation Model for End-to-End Extreme Observation and Reconstruction

Applied Sciences, 2022
Data transmission and storage are inseparable from compression technology. Compressed sensing directly undersamples and reconstructs data at a much lower sampling frequency than Nyquist, which reduces redundant sampling.
Han Diao, Xiaozhu Lin, Chun Fang
doaj   +1 more source