High performance optical encryption based on computational ghost imaging with QR code and compressive sensing technique

2015 ◽  
Vol 353 ◽  
pp. 90-95 ◽  
Author(s):  
Shengmei Zhao ◽  
Le Wang ◽  
Wenqiang Liang ◽  
Weiwen Cheng ◽  
Longyan Gong
Keyword(s):  
Compressive Sensing ◽  
High Performance ◽  
Qr Code ◽  
Ghost Imaging ◽  
Optical Encryption

Image quality enhancement in low-light-level ghost imaging using modified compressive sensing method

2018 ◽  
Vol 15 (4) ◽  
pp. 045204 ◽  
Author(s):  
Xiaohui Shi ◽  
Xianwei Huang ◽  
Suqin Nan ◽  
Hengxing Li ◽  
Yanfeng Bai ◽  
...  
Keyword(s):  
Image Quality ◽  
Compressive Sensing ◽  
Light Level ◽  
Quality Enhancement ◽  
Ghost Imaging ◽  
Low Light ◽  
Image Quality Enhancement

Multi-image encryption based on QR code and singular value decomposition ghost imaging

2022 ◽  
Author(s):  
Miao Wang ◽  
Xiulun Yang ◽  
Xiangfeng Meng ◽  
Yurong Wang ◽  
Yongkai Yin ◽  
...  
Keyword(s):  
Singular Value Decomposition ◽  
Image Encryption ◽  
Singular Value ◽  
Qr Code ◽  
Ghost Imaging ◽  
Value Decomposition

Influence of two-arm symmetry on reconstructed image of compressive sensing for ghost imaging

2014 ◽  
Vol 22 (6) ◽  
pp. 1438-1445
Author(s):  
王铭海 WANG Ming-hai ◽  
曹军胜 CAO Jun-sheng ◽  
郜峰利 GAO Feng-li
Keyword(s):  
Compressive Sensing ◽  
Reconstructed Image ◽  
Ghost Imaging

Grayscale and color ghost-imaging of moving objects by memory-enabled, memoryless and compressive sensing algorithms

2019 ◽  
Vol 21 (8) ◽  
pp. 085709
Author(s):  
Sahar Gholami-milani ◽  
Babak Olyaeefar ◽  
Sohrab Ahmadi-kandjani ◽  
Reza Kheradmand
Keyword(s):  
Compressive Sensing ◽  
Moving Objects ◽  
Ghost Imaging

Compressive sensing ghost imaging object detection using generative adversarial networks

2019 ◽  
Vol 58 (01) ◽  
pp. 1 ◽  
Author(s):  
Xiang Zhai ◽  
Zhengdong Cheng ◽  
Yuan Wei ◽  
Zhenyu Liang ◽  
Yi Chen
Keyword(s):  
Object Detection ◽  
Compressive Sensing ◽  
Generative Adversarial Networks ◽  
Ghost Imaging ◽  
Adversarial Networks

Secure optical encryption based on ghost imaging with fractional Fourier transform

2020 ◽  
Vol 474 ◽  
pp. 126086
Author(s):  
Shengmei Zhao ◽  
Xiaodi Yu ◽  
Le Wang ◽  
Wei Li ◽  
Baoyu Zheng
Keyword(s):  
Fourier Transform ◽  
Fractional Fourier Transform ◽  
Ghost Imaging ◽  
Optical Encryption

scholarly journals High-Performance 3D Compressive Sensing MRI Reconstruction Using Many-Core Architectures

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
Daehyun Kim ◽  
Joshua Trzasko ◽  
Mikhail Smelyanskiy ◽  
Clifton Haider ◽  
Pradeep Dubey ◽  
...  
Keyword(s):  
Compressive Sensing ◽  
High Performance ◽  
State Of The Art ◽  
Sparse Signals ◽  
Mri Scan ◽  
Nyquist Criterion ◽  
Mri Reconstruction ◽  
Computationally Intensive ◽  
Many Core ◽  
Significant Attention

Compressive sensing (CS) describes how sparse signals can be accurately reconstructed from many fewer samples than required by the Nyquist criterion. Since MRI scan duration is proportional to the number of acquired samples, CS has been gaining significant attention in MRI. However, the computationally intensive nature of CS reconstructions has precluded their use in routine clinical practice. In this work, we investigate how different throughput-oriented architectures can benefit one CS algorithm and what levels of acceleration are feasible on different modern platforms. We demonstrate that a CUDA-based code running on an NVIDIA Tesla C2050 GPU can reconstruct a 256 × 160 × 80 volume from an 8-channel acquisition in 19 seconds, which is in itself a significant improvement over the state of the art. We then show that Intel's Knights Ferry can perform the same 3D MRI reconstruction in only 12 seconds, bringing CS methods even closer to clinical viability.

Optical encryption based on computational ghost imaging

2010 ◽  
Vol 35 (14) ◽  
pp. 2391 ◽  
Author(s):  
Pere Clemente ◽  
Vicente Durán ◽  
Víctor Torres-Company ◽  
Enrique Tajahuerce ◽  
Jesús Lancis
Keyword(s):  
Ghost Imaging ◽  
Optical Encryption
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