Snapshot compressive imaging: Theory, algorithms, and applications
Capturing high-dimensional (HD) data is a long-term challenge in signal processing and
related fields. Snapshot compressive imaging (SCI) uses a 2D detector to capture HD (≥ …
related fields. Snapshot compressive imaging (SCI) uses a 2D detector to capture HD (≥ …
Deep learning in electron microscopy
JM Ede - Machine Learning: Science and Technology, 2021 - iopscience.iop.org
Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …
microscopy. This review paper offers a practical perspective aimed at developers with …
Plug-and-play algorithms for large-scale snapshot compressive imaging
Snapshot compressive imaging (SCI) aims to capture the high-dimensional (usually 3D)
images using a 2D sensor (detector) in a single snapshot. Though enjoying the advantages …
images using a 2D sensor (detector) in a single snapshot. Though enjoying the advantages …
Group sparsity residual constraint with non-local priors for image restoration
Group sparse representation (GSR) has made great strides in image restoration producing
superior performance, realized through employing a powerful mechanism to integrate the …
superior performance, realized through employing a powerful mechanism to integrate the …
Effective snapshot compressive-spectral imaging via deep denoising and total variation priors
Snapshot compressive imaging (SCI) is a new type of compressive imaging system that
compresses multiple frames of images into a single snapshot measurement, which enjoys …
compresses multiple frames of images into a single snapshot measurement, which enjoys …
Efficient and secure image communication system based on compressed sensing for IoT monitoring applications
L Li, G Wen, Z Wang, Y Yang - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The Internet of Things (IoT) has attracted extensive attention in the information field. Its rapid
development has promoted several monitoring application domains. However, the resource …
development has promoted several monitoring application domains. However, the resource …
A highly robust reversible watermarking scheme using embedding optimization and rounded error compensation
Y Tang, S Wang, C Wang, S Xiang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The robust reversible watermarking (RRW) requires high robustness and capacity on the
condition of reversibility and imperceptibility, which still remains a big challenge nowadays …
condition of reversibility and imperceptibility, which still remains a big challenge nowadays …
Guided ultrasonic waves propagation imaging: a review
This article presents a comprehensive review of the laser-based guided ultrasonic waves
propagation imaging (G-UPI) system and respective signal/data processing methods related …
propagation imaging (G-UPI) system and respective signal/data processing methods related …
Ams-net: Adaptive multi-scale network for image compressive sensing
Recently, deep convolutional neural networks have been applied to image compressive
sensing (CS) to improve reconstruction quality while reducing computation cost. Existing …
sensing (CS) to improve reconstruction quality while reducing computation cost. Existing …
An optimal adaptive reweighted sampling-based adaptive block compressed sensing for underwater image compression
R Monika, S Dhanalakshmi - The Visual Computer, 2023 - Springer
Abstract The use of Block Compressed Sensing (BCS) as an alternative to conventional
Compressed Sensing (CS) in image sampling and acquisition has gained attention due to …
Compressed Sensing (CS) in image sampling and acquisition has gained attention due to …