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Learning-Based Sparse Data reconstruction for Compressed Data Aggregation in IoT Networks

IEEE INTERNET OF THINGS JOURNAL 2021年第14期8卷 11732-11742页

作者： Zhang, Mingqiang Zhang, Haixia Yuan, Dongfeng Zhang, Minggao Shandong Univ Shandong Prov Key Lab Wireless Commun Technol Jinan 250061 Peoples R China Shandong Univ Shandong Prov Key Lab Wireless Commun Technol Jinan 250061 Peoples R China Shandong Univ Sch Control Sci & Engn Jinan 250061 Peoples R China

Due to the booming of various devices in Internet-of-Things (IoT) networks, more data should be transmitted over the networks, which will thereby consume more transmission bandwidth and more transmit power. Compressed data aggregation (CDA) has been proposed as an effective way to reduce the amount of the collected data in IoT networks. Although adopting compressed sensing (CS), CDA can sample the source data efficiently, and sparse data reconstruction is still a big challenge. In this work, inspired by this, we propose a learning-based sparse data reconstruction scheme by jointly utilizing CS and deep learning. Our objective is to reduce the volume of data to be transmitted over IoT networks without losing reconstruction accuracy. A deep CS network is designed by adopting an end-to-end learning method to build a measurement matrix and an efficient and high-accuracy reconstruction network. To show the performance of the proposed scheme, six data sets with different structured sparse models and a real sensor data set are utilized in doing experiments. The performance of the proposed scheme in terms of mean-squared error, peak-signal-noise-ratio, and structural similarity is investigated. The results demonstrate the effectiveness of the proposed scheme in reconstruction accuracy for given compression ratio. The results also show that the proposed scheme is suitable for the process of CDA, thus can effectively reduce the amount of data to be transmitted in IoT networks.

关键词： Data aggregation Internet of Things Sparse matrices Data communication reconstruction algorithms Matching pursuit algorithms Data acquisition Compressed data aggregation (CDA) compressed sensing (CS) data reconstruction deep learning Internet of Things (IoT)

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Research on parameterized modeling and generation of Chinese Chainmail pattern 4

Research on parameterized modeling and generation of Chinese...

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4th International Conference on Computer Graphics, Image, and Virtualization, ICCGIV 2024

作者： Wang, Zhen Zhang, Pengsong Zhu, Siyuan Lei, Qian Sun, Shunyao Institute of Interdisciplinary Studies Hunan Normal University Changsha410023 China College of Engineering and Design Hunan Normal University Changsha410023 China

ISBN: (纸本)9781510683242

The Chinese chainmail pattern has a rich historical lineage, constituting a mathematically precise and aesthetically ordered geometric manifestation originating from ancient chainmail armor. It stands as an exemplar among the traditional Chinese patterns. However, contemporary research on the Chinese chainmail pattern confronts challenges associated with its insufficient cultural connotation, deficient parameter expression methods, and a notable absence of modern design transformation and innovation. In the era of booming digitization and the Internet, the integration of computer technology into the inventive redesign of geometric traditional patterns, with the Chinese chainmail pattern being a striking example, has the potential to breathe life into these ancient patterns within the framework of modern design. This not only revitalizes traditional patterns but also makes them more prolific and easy to communication and application. This article positions the developmental trajectory of the Chinese chainmail pattern as its inception point. By methodically enhancing its reconstruction and iterating digitally using parametric techniques, this study attempts to amalgamate the traditional Chinese chainmail pattern with contemporary design paradigms. This amalgamation is subsequently applied to the field of modern product design, thus offering novel perspectives and innovative approaches for the transformation of modern design. © 2024 SPIE.

关键词： Design Visualization Mathematical modeling Modeling Data modeling Product engineering reconstruction algorithms Chemical elements Engineering Reflection

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Channeled imaging spectropolarimeter reconstruction by neural networks

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OPTICS EXPRESS 2021年第22期29卷 35556-35569页

作者： Lv, Xiaobo Yang, Zhihui Wang, Yifei Zhou, Keya Lin, Jie Jin, Peng Harbin Inst Technol Key Lab Microsyst & Microstruct Mfg Minist Educ Harbin 150080 Peoples R China Harbin Inst Technol Sch Instrumentat Sci & Engn Harbin 150080 Peoples R China Beijing Inst Technol Sch Opt & Photon Beijing 100081 Peoples R China Harbin Inst Technol Sch Phys Harbin 150080 Peoples R China

Snapshot channeled imaging spectropolarimetry (SCISP), which can achieve spectral and polarization imaging without scanning (a single exposure), is a promising optical technique. As Fourier transform is used to reconstruct information, SCISP has its inherent limitations such as channel crosstalk, resolution and accuracy drop, the complex phase calibration, et al. To overcome these drawbacks, a nonlinear technique based on neural networks (NNs) is introduced to replace the role of Fourier reconstruction. Herein, abundant spectral and polarization datasets were built through specially designed generators. The established NNs can effectively learn the forward conversion procedure through minimizing a loss function, subsequently enabling a stable output containing spectral, polarization, and spatial information. The utility and reliability of the proposed technique is confirmed by experiments, which are proved to maintain high spectral and polarization accuracy. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

关键词： Fourier transforms High throughput optics Imaging systems Neural networks Real time implementation reconstruction algorithms

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QSM reconstruction challenge 2.0: Design and report of results

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MAGNETIC RESONANCE IN MEDICINE 2021年第3期86卷 1241-1255页

作者： Bilgic, Berkin Langkammer, Christian Marques, Jose P. Meineke, Jakob Milovic, Carlos Schweser, Ferdinand Athinoula A Martinos Ctr Biomed Imaging Charlestown MA USA Harvard Med Sch Dept Radiol Boston MA USA MIT Harvard MIT Hlth Sci & Technol Cambridge MA 02139 USA Med Univ Graz Dept Neurol Graz Austria Radboud Univ Nijmegen Donders Ctr Cognit Neuroimaging Nijmegen Netherlands Philips Res Hamburg Germany Pontificia Univ Catolica Chile Dept Elect Engn Santiago Chile Pontificia Univ Catolica Chile Biomed Imaging Ctr Santiago Chile UCL Dept Med Phys & Biomed Engn London England Univ Buffalo Buffalo Neuroimaging Anal Ctr Jacobs Sch Med & Biomed Sci Dept NeurolState Univ New York Buffalo NY USA Univ Buffalo State Univ New York Ctr Biomed Imaging Clin & Translat Sci Inst Buffalo NY USA

Purpose: The aim of the second quantitative susceptibility mapping (QSM) reconstruction challenge (Oct 2019, Seoul, Korea) was to test the accuracy of QSM dipole inversion algorithms in simulated brain data. Methods: A two-stage design was chosen for this challenge. The participants were provided with datasets of multi-echo gradient echo images synthesized from two realistic in silico head phantoms using an MR simulator. At the first stage, participants optimized QSM reconstructions without ground truth data available to mimic the clinical setting. At the second stage, ground truth data were provided for parameter optimization. Submissions were evaluated using eight numerical metrics and visual ratings. Results: A total of 98 reconstructions were submitted for stage 1 and 47 submissions for stage 2. Iterative methods had the best quantitative metric scores, followed by deep learning and direct inversion methods. Priors derived from magnitude data improved the metric scores. algorithms based on iterative approaches and total variation (and its derivatives) produced the best overall results. The reported results and analysis pipelines have been made public to allow researchers to compare new methods to the current state of the art. Conclusion: The synthetic data provide a consistent framework to test the accuracy and robustness of QSM algorithms in the presence of noise, calcifications and minor voxel dephasing effects. Total Variation-based algorithms produced the best results among all metrics. Future QSM challenges should assess whether this good performance with synthetic datasets translates to more realistic scenarios, where background fields and dipole-incompatible phase contributions are included.

关键词： assessment challenge dipole inversion quantitative susceptibility mapping reconstruction algorithms

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TFR Recovery From Incomplete Micro-Doppler Signal via AL-ADMM-Net

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IEEE ACCESS 2022年 10卷 107395-107401页

作者： Yuan, Yanxin Luo, Ying Zhang, Qun Zhang, Cong Air Force Engn Univ Inst Informat & Nav Xian 710077 Peoples R China Collaborat Innovat Ctr Informat Sensing & Underst Xian 710077 Peoples R China Fudan Univ Minist Educ Key Lab Informat Sci Electromagnet Waves Shanghai 200433 Peoples R China

The micro-motion target echoes can be regarded as the accumulation of a few strong scattering points echoes, which are naturally sparse. Therefore, the compressed sensing (CS) reconstruction method can be used to analyze the incomplete micro-Doppler signal and extract the micro-motion features. Traditional CS reconstruction algorithms are time-consuming and sensitive to the selection of model parameters, limiting the performance of micro-motion feature extraction. This paper proposes a deep unfolded method to achieve the reconstruction of the time-frequency representation (TFR) of incomplete micro-Doppler signals. First, the joint time-frequency (JTF) transform is used to construct the CS model and the Training data is obtained according to the model. Then, the alternating direction method of multipliers (ADMM) algorithm is constructed into an iterative network named ADMM-net corresponding to the iterative solution process. An auxiliary loss is designed into the ADMM-net called AL-ADMM-net to improve the quality of reconstruction. The AL-ADMM-net is trained by the training data to learn the optimal parameters. Furthermore, an AL-ADMM-net iterative method is proposed when the micro-Doppler signal has phase corruption. Simulations are given to prove the effectiveness of the proposed method.

关键词： Feature extraction Time-frequency analysis Radar Scattering Image reconstruction Deep learning reconstruction algorithms Doppler radar Compressed sensing Compressed sensing micro-doppler ADMM-net deep learning auxiliary loss

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Near optical coaxial phase measuring deflectometry for measuring structured specular surfaces

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OPTICS EXPRESS 2022年第10期30卷 17554-17566页

作者： Gao, Feng Xu, Yongjia Jiang, Xiangqian Univ Huddersfield EPSRC Future Metrol Hub Huddersfield HD1 3DH W Yorkshire England

Phase measuring deflectometry (PMD) is an important technique for the form measurement of specular surfaces. However, the existing stereo-PMD techniques have noticeable weaknesses for structured specular surfaces measurement due to the optical axis of the imaging system must have a notable intersection angle with the optical axis of the display system according to the law of reflection. This leads to the imaging sensor and the fringe display screen must be located on the opposite sides of the normal of the surface under test (SUT), which results in large system volume and measurement shadows when measuring discontinuous specular surfaces. In this paper, we propose a novel near optical coaxial PMD (NCPMD) by utilizing a plate beamsplitter. With the assistance of plate beamsplitter, the optical axis of display screen can be configured much closer to the optical axis of the imaging system which makes the system more compact and has significantly reduced volume compared with the conventional PMD configuration. Moreover, imaging sensors in the proposed configuration can perpendicularly capture the SUT, which can drastically decrease measurement shadows caused by discontinuous structures on the SUT and increases measurement efficiency. A comparison between the proposed NCPMD and the conventional PDM is studied by measuring a specular step to show the advantage of the proposed configuration in reducing measurement error caused by structure shadows. A portable NCPMD prototype with stereo imaging sensors is developed and verified through experiments. Experimental results show the portable prototype has comparable measurement accuracy with the existing PMD techniques while has obviously advanced performances for portable and embedded form measurement, such as small system volume, and light weight.

关键词： Freeform surfaces Image sensors Laser pointers Optical components reconstruction algorithms Surface measurements

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Variable electro-optic shearing interferometry for ultrafast single-photon-level pulse characterization

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OPTICS EXPRESS 2022年第22期30卷 39826-39839页

作者： Kurzyna, Stanislaw Jastrzebski, Marcin Fabre, Nicolas Wasilewski, Wojciech Lipka, Michal Parniak, Michal Univ Warsaw Ctr Quantum Opt Technol Ctr New Technol Banacha 2c PL-02097 Warsaw Poland Univ Warsaw Fac Phys Pasteura 5 PL-02093 Warsaw Poland Univ Complutense Fac Fis Dept Opt Madrid 28040 Spain Univ Copenhagen Niels Bohr Inst Blegdamsvej 17 DK-2100 Copenhagen Denmark

Despite the multitude of available methods, the characterization of ultrafast pulses remains a challenging endeavor, especially at the single-photon level. We introduce a pulse characterization scheme that maps the magnitude of its short-time Fourier transform. Contrary to many well-known solutions it does not require nonlinear effects and is therefore suitable for single-photon-level measurements. Our method is based on introducing a series of controlled time and frequency shifts, where the latter is performed via an electro-optic modulator allowing a fully-electronic experimental control. We characterized the full spectral and temporal width of a classical and single-photon-level pulse and successfully tested the applicability of the reconstruction algorithm of the spectral phase and amplitude. The method can be extended by implementing a phase-sensitive measurement and is naturally well-suited to partially-incoherent light.

关键词： Fourier transforms Industrial optical metrology Interferometry Nonlinear effects reconstruction algorithms Shearing interferometry

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Co-optimization method to improve lateral resolution in photoacoustic computed tomography

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BIOMEDICAL OPTICS EXPRESS 2022年第9期13卷 4621-4636页

作者： Zhang, Yang Yang, Shufan Xia, Zhiying Hou, Ruijie Xu, Bin Hou, Lianping Marsh, John H. Hou, Jamie Jiangmin Rezaelsan, Seyed Mojtaba Liu, Xuefeng Xiong, Jichuan Nanjing Univ Sci & Technol Sch Elect & Opt Engn Nanjing 210094 Peoples R China Edinburgh Napier Univ Sch Comp Edinburgh EH10 5DT Scotland Univ Glasgow James Watt Sch Engn Glasgow G12 8QQ Scotland Royal Coll Surg Edinburgh Nicolson St Edinburgh EH8 9DW Scotland Islamic Azad Univ Dept Phys North Tehran Branch Tehran *** Iran

In biomedical imaging, photoacoustic computed tomography (PACT) has recently gained increased interest as this imaging technique has good optical contrast and depth of acoustic penetration. However, a spinning blur will be introduced during the image reconstruction process due to the limited size of the ultrasonic transducers (UT) and a discontinuous measurement process. In this study, a damping UT and adaptive back-projection co-optimization (CODA) method is developed to improve the lateral spatial resolution of PACT. In our PACT system, a damping aperture UT controls the size of the receiving area, which suppresses image blur at the signal acquisition stage. Then, an innovative adaptive back-projection algorithm is developed, which corrects the undesirable artifacts. The proposed method was evaluated using agar phantom and ex-vivo experiments. The results show that the CODA method can effectively compensate for the spinning blur and eliminate unwanted artifacts in PACT. The proposed method can significantly improve the lateral spatial resolution and image quality of reconstructed images, making it more appealing for wider clinical applications of PACT as a novel, cost-effective modality. Published by Optica Publishing Group under the terms of the Creative Commons Attribution 4.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.

关键词： High numerical aperture optics Image processing Image quality Medical imaging reconstruction algorithms Spatial resolution

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Towards practical holographic coherent diffraction imaging via maximum likelihood estimation

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OPTICS EXPRESS 2022年第5期30卷 6886-6906页

作者： Barmherzig, David A. Sun, Ju Flatiron Inst Ctr Computat Math 162 Fifth Ave New York NY 10010 USA Univ Minnesota Dept Comp Sci & Engn 200 Union St SE Minneapolis MN 55455 USA

A new algorithmic framework is developed for holographic coherent diffraction imaging (HCDI) based on maximum likelihood estimation (MLE). This method provides superior image reconstruction results for various practical HCDI settings, such as when data is highly corrupted by Poisson shot noise and when low-frequency data is missing due to occlusion from a beamstop apparatus. This method is also highly robust in that it can be implemented using a variety of standard numerical optimization algorithms, and requires fewer constraints on the physical HCDI setup compared to current algorithms. The mathematical framework developed using MLE is also applicable beyond HCDI to any holographic imaging setup where data is corrupted by Poisson shot noise. (C) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

关键词： Image quality Image reconstruction Inverse problems Phase retrieval Photon counting reconstruction algorithms

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Performing tomographic reconstructions from a satellite looking toward Earth. Part 2: analysis of image quality

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JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION 2022年第7期39卷 1282-1288页

作者： Hinton, Garrett W. Latvakoski, Harri Taylor, Michael Clarkson, Eric Kupinski, Matthew A. Hancock, Jed Space Dynam Lab North Logan UT 84341 USA Univ Arizona Coll Opt Sci Tucson AZ 85721 USA Univ Arizona Ctr Gamma Ray Imaging Dept Med Imaging Tucson AZ 85724 USA

This paper is part 2 of two papers that explore performing tomographic reconstructions from a space platform. A simplified model of short-wave infrared emissions in the atmosphere is given. Simulations were performed that tested the effectiveness of reconstructions given signal amplitude, frequency, signal-to-noise ratio, number of iterations run, and others. Maximum likelihood expectation maximization is shown to be effective for reconstructing low signal cases. (C) 2022 Optica Publishing Group

关键词： Image quality Image reconstruction Imaging systems reconstruction algorithms Systems design Three dimensional reconstruction

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