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Compressive sensed video recovery via iterative thresholding with random transforms

Published:2020-04-10 Issue:6 Volume:14 Page:1187-1199
ISSN:1751-9659
Container-title:IET Image Processing
language:en
Short-container-title:IET image process

Author:

Belyaev Evgeny¹^ORCID,Codreanu Marian²,Juntti Markku³^ORCID,Egiazarian Karen⁴

Affiliation:

1. International Laboratory ‘Computer Technologies’ITMO University197101Saint‐PetersburgRussia

2. Department of Science and TechnologyLinköping University581 83LinköpingSweden

3. Centre for Wireless CommunicationsOulu University90014OuluFinland

4. Department of Signal ProcessingTampere University33720TampereFinland

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2019.0661

Reference25 articles.

1. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information

2. Compressed sensing

3. Compressive Sensing on a CMOS Separable-Transform Image Sensor

4. Single‐pixel compressive imaging based on motion compensation

5. Video Compressive Sensing Reconstruction via Reweighted Residual Sparsity

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Compressive Sensed Video Recovery Using Iterative Thresholding with Quality Enhancing Neural Networks;2024 26th International Conference on Digital Signal Processing and its Applications (DSPA);2024-03-27

2. MsDC-DEQ-Net: Deep Equilibrium Model (DEQ) with Multiscale Dilated Convolution for Image Compressive Sensing (CS);IET Signal Processing;2024-01-18

3. A Novel Complex-Valued Gaussian Measurement Matrix for Image Compressed Sensing;Entropy;2023-08-22

4. An Efficient Compressive Sensed Video Codec with Inter-Frame Decoding and Low-Complexity Intra-Frame Encoding;Sensors;2023-01-26

5. A High-Quality Adaptive Video Reconstruction Optimization Method Based on Compressed Sensing;Computer Modeling in Engineering & Sciences;2023

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