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Single-shot blind deconvolution with coded aperture

APPLIED OPTICS 2022年第22期61卷 6408-6413页

作者： Muneta, Hideyuki Horisaki, Ryoichi Nishizaki, Yohei Naruse, Makoto Tanida, Jun Osaka Univ Grad Sch Informat Sci & Technol Dept Informat & Phys Sci 1-5 Yamadaoka Suita Osaka 5650871 Japan Univ Tokyo Grad Sch Informat Sci & Technol Dept Informat Phys & Comp Bunkyo Ku 7-3-1 Hongo Tokyo 1138656 Japan Osaka Res Inst Ind Sci & Technol Environm Technol Res Div Syst & Control Lab Joto Ku 1-6-50 Morinomiya Osaka 5368553 Japan

In this paper, we present a method for single-shot blind deconvolution incorporating a coded aperture (CA). In this method, we utilize the CA, inserted on the pupil plane, as support constraints in blind deconvolution. Not only an object is estimated, but also a point spread function of turbulence from a single captured image by a reconstruction algorithm with CA support. The proposed method is demonstrated by simulation and an experiment in which point sources are recovered under severe turbulence. (C) 2022 Optica Publishing Group

关键词： Aperture synthesis Atmospheric turbulence Blind deconvolution Imaging systems Optical imaging reconstruction algorithms

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An Effective Pattern reconstruction Method for the Under-Sampled High-Frequency Planar Near Fields

An Effective Pattern Reconstruction Method for the Under-Sam...

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Antennas and Propagation & USNC/URSI National Radio Science Meeting

作者： Junhao Zheng Zhengpeng Wang Xiaoming Chen School of Information and Communications Engineering Xi'an Jiaotong University China School of Electronic Information Engineering Beihang University China

This paper presents an accurate and efficient method to reconstruct the far-field pattern of the under-sampled high-frequency planar near field for the antenna under test based on the asymptotic field similarity theor... 详细信息

ISBN: (数字)9798350369908

ISBN: (纸本)9798350369915

关键词： Accuracy Antenna theory Conferences reconstruction algorithms Antennas and propagation

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A New reconstruction Method for a Source Above an Arbitrarily Shaped Ground Plane

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IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY 2021年第2期63卷 627-630页

作者： Zhong, Yang Enomoto, Takashi Seto, Shingo Araki, Kenji Hwang, Chulsoon Duke Univ Durham NC 27708 USA Missouri Univ Sci & Technol EMC Lab Rolla MO 65401 USA Sony Global Mfg & Operat Corp Minato Ku Konan 1080075 Japan

Source reconstruction using equivalent dipole moments to replace the original noise source is widely used in radio frequency interference. The conventional reconstruction methods only work well in the cases of free space or with a large ground plane. In this article a new method is proposed for source reconstruction over an arbitrarily shaped ground plane. It uses the field below the ground plane to eliminate the arbitrary ground effect. Comparing to the method of solving surface integral equation, it is simple and does not need the ground geometric information. The new method is validated in the full-wave simulations.

关键词： Image reconstruction reconstruction algorithms Mathematical model Surface reconstruction Integral equations Scattering Current density Image theorem radio frequency interference (RFI) source reconstruction surface equivalence theorem

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Research on power purchase forecasting technology based on EEMD-GRU-RF 9

Research on power purchase forecasting technology based on E...

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9th International Conference on Energy Materials and Electrical Engineering, ICEMEE 2023

作者： Li, Xiaomin Sun, Ming Li, Yu Wang, Yuanyuan State Grid Xuchang Power Supply Company Henan Xuchang450000 China

ISBN: (纸本)9781510672765

The power purchase forecast can help the power system make reasonable power pre-purchase plans and achieve scientific coordination of grid planning and construction. This paper proposes a forecast model of power purchase based on EEMD-GRU-RF. The model first decomposes the original power purchase series into high and low frequency components using EEMD, and then selects the random forest algorithm to predict the low frequency components of power purchase using meteorological, fault work order, historical power consumption series and holiday information as features, and uses GRU network to achieve the prediction of high frequency eigenmodes, and finally reconstructs the superposition of both to achieve power purchase prediction. The experimental results show that the evaluation indexes RMSE, MAE and R2 of the proposed algorithm are 0.019, 0.011 and 0.976, respectively, which are better than other mainstream power purchase prediction algorithms and can achieve higher accuracy of power purchase prediction. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Modal decomposition Education and training Power consumption Deep learning reconstruction algorithms Power grids Random forests Sampling rates

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Off-axis image plane hologram compression in holographic tomography - metrological assessment

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OPTICS EXPRESS 2022年第3期30卷 4261-4273页

作者： Muhamad, R. K. Stcpie, P. Kujawinska, M. Schelkens, P. Vrije Univ Brussel VUB Dept Elect & Informat ETRO Pl Laan 2 B-1050 Brussels Belgium IMEC Kapeldreef 75 B-3001 Leuven Belgium Warsaw Univ Technol Inst Micromech & Photon Ul Sw A Boboli 8 PL-02525 Warsaw Poland

In this paper, we present a novel study on the impact of lossy data compression on the metrological properties of holographic tomography reconstruction of the refractive index (RI). We use a spatial bandwidth-optimized compression procedure that leverages the properties of image plane off-axis holograms and standardized compression codecs, both widely applied in research and industry. The compression procedure is tested at multiple bitrates, for four different objects and against three reconstruction algorithms. The metrological evaluation is primarily done by comparison to the reconstruction from original data using the root-mean-squared error (RMSE). We show that due to differences between objects and different noise sensitivities of the reconstruction algorithms, the rate-distortion behaviour varies, but in most cases allows for the compression below 1 bit per pixel, while maintaining an RI RMSE less than 10(-4). (C) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

关键词： Discrete Fourier transforms Holographic microscopy Holographic techniques Image reconstruction Phase retrieval reconstruction algorithms

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Characterization of surface defects using a phase retrieval technique in a high-power laser system

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APPLIED OPTICS 2022年第6期61卷 1545-1551页

作者： Lehmann, Lucien Bouillet, Stephane Leymarie, Christophe Ameil-Schuh, Christel Benoit, Melusine Rouyer, Claude Ctr Etud Sci & Tech Aquitaine Commissariat Energie Atom & Energies Alternat F-33116 Le Barp France

In the framework of high-power lasers, surface defects on optics can generate strong light intensification and induce damage sites on downstream optics. To evaluate this intensification during high-energy laser shots, a three-step method is proposed. First, a dedicated measurement bench is designed to measure the intensification induced by defects on a wide variety of optics, including amplifier slabs, KDP crystals, mirrors, gratings, and vacuum windows, for propagation distances up to 2000 mm.A multi-resolution single-beam multiple-intensity reconstruction phase retrieval algorithm is then used to reconstruct a model of the defect, in both amplitude and phase, from a set of intensification measurements. Finally, the impact of the modeled defect on downstream optics is evaluated with a simulation of the high-power laser system. This method is experimentally validated through a case study of damage identified on one of the Laser Migajoule (LMJ) beams, characterized with the method presented in this paper. The long-distance impact on the LMJ beam is estimated by simulation and compared to a direct near-field measurement. (C) 2022 Optica Publishing Group

关键词： High power lasers Laser damage Laser fusion Optical components Phase retrieval reconstruction algorithms

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Pseudo Quad-Pol Simulation From Compact Polarimetric SAR Data via a Complex-Valued Dual-Branch Convolutional Neural Network

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2022年 15卷 901-918页

作者： Zhang, Fan Cao, Zhuoyue Xiang, Deliang Hu, Canbin Ma, Fei Yin, Qiang Zhou, Yongsheng Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing 100029 Peoples R China Beijing Univ Chem Technol Interdisciplinary Res Ctr Artificial Intelligence Beijing 100029 Peoples R China Beijing Univ Chem Technol Beijing Adv Innovat Ctr Soft Matter Sci & Engn Beijing 100029 Peoples R China

Compact polarimetry (CP) has attracted much attention in recent years due to its hybrid dual-polarization imaging mode. CP synthetic aperture radar has a larger swath and can provide more polarimetric information compared with the traditional dual-polarization imaging mode (HH/HV or VH/VV). Pseudo quad-polarimetric (quad-pol) data reconstruction is an important technology in the application of CP data. The goal of pseudo quad-pol data reconstruction from CP data is to change the form of CP data to the form of quad-pol data without increasing any new information. In this article, a new pseudo quad-pol data reconstruction method from the CP data is proposed. This method combines a complex-valued dual-branch convolutional neural network (CV-DBCNN) to achieve the reconstruction of the pseudo quad-pol data. It utilizes complex-valued convolutional layers and a complex-valued activation function to fully extract the polarimetric information embedded in the complex-valued CP data. For the CV-DBCNN, the branch with 1x1 kernel size is used to nonlinearly and self-adaptively combine the channel of input data, and the branch with 3x3 kernel size is used to extract the discriminative regional polarimetric features. Furthermore, polarimetric decomposition is utilized to evaluate the scattering mechanisms of the pseudo quad-pol data. Three state-of-the-art methods are utilized for comparison. In comparison with other methods, our proposed reconstruction method based on the CV-DBCNN shows its superiority in terms of the pseudo quad-pol data reconstruction and scattering mechanism preservation.

关键词： Image reconstruction Synthetic aperture radar Feature extraction Scattering reconstruction algorithms Covariance matrices Kernel Compact polarimetry (CP) complex-valued dual-branch convolutional neural network (CV-DBCNN) deep learning pseudo quad-polarization (quad-pol) data reconstruction synthetic aperture radar (SAR)

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Video Snapshot Compressive Imaging Using Residual Ensemble Network

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2022年第9期32卷 5931-5943页

作者： Sun, Yubao Chen, Xunhao Kankanhalli, Mohan S. Liu, Qingshan Li, Junxia Minist Educ Engn Res Ctr Digital Forens Nanjing 210044 Peoples R China Nanjing Univ Informat Sci & Technol Collaborat Innovat Ctr Atmospher Environm & Equip Nanjing 210044 Peoples R China Southeast Univ Sch Automat Nanjing 210096 Peoples R China Natl Univ Singapore Sch Comp Singapore 117427 Singapore

Video snapshot compressive imaging (SCI) system enables high-frame-rate imaging by projecting multiple frames into a 2D snapshot measurement during a single exposure, and the original video frames can be reconstructed by solving an optimization problem. However, existing methods usually cannot achieve a good balance between reconstruction time and reconstruction quality, which has become a major obstacle for practical application of video SCI. In order to cope with this issue, we propose a residual ensemble network to learn the explicit inverse mapping from the 2D snapshot measurement to the original video. Specifically, the proposed network aims to exploit the spatiotemporal correlations between video frames for improving reconstruction quality. The spatiotemporal correlations of video frames demonstrate multiple types, including intra-frame spatial correlation, inter-frame forward and backward temporal correlation. With the purpose of fully capturing these differentiated correlations, we design four sub-networks, namely, a pseudo-3D U-shape sub-network, two residual sub-networks, and a serial forward and backward recurrent sub-network, and further assemble these four sub-networks into an ensemble network through alternate residual links. This ensemble network can effectively fuse the predictions of each sub-network and maintain spatiotemporal consistency between video frames. We further design a compound loss function to guide the network learning, and the new video can be fast reconstructed by simply feeding its 2D snapshot measurement into the learned network. The experimental results demonstrate that our network can significantly improve the reconstruction quality while maintaining low computational cost.

关键词： Image reconstruction Correlation Imaging Spatiotemporal phenomena reconstruction algorithms Streaming media Optimization Snapshot compressive imaging residual ensemble serial recurrent network spatiotemporal correlations

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Electric power personnel safety monitoring method based on intelligent image processing 4

Electric power personnel safety monitoring method based on i...

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4th International Conference on Testing Technology and Automation Engineering, TTAE 2024

作者： Yan, Nannan Feng, Jianfeng Xue, Xiangyang Su, Lei Chen, Yan State Grid Shanghai Electric Power Company Shanghai200122 China Institute of Brain and Intelligence Science and Technology School of Computer Science Fudan University Shanghai200433 China

ISBN: (数字)9781510686656

ISBN: (纸本)9781510686649

In this work, an intelligent monitoring method based on target detection and pose estimation is proposed for personal protective equipment monitoring and deep analysis of safety behavior. Different from previous image processing methods, this work uses object detection algorithm to calculate the types and positions of operators and security tools in image data. The pose estimation algorithm is introduced to calculate the key points of the human skeleton in the image data and identify the human pose, and then the relative position relationship of the key point coordinates is compared to analyze and judge the pose of the operator. The experimental results show that the intelligent monitoring method proposed in this work can improve the safety protection effect of operators to the greatest extent on the premise of ensuring the smooth completion of operations. © 2024 SPIE.

关键词： Safety Object detection Target detection Pose estimation Detection and tracking algorithms Data modeling Image processing Education and training Head reconstruction algorithms

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I2IP: image to image editing with prompt control using guided diffusion models 4

I2IP: image to image editing with prompt control using guide...

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4th International Conference on Computer Vision and Pattern Analysis, ICCPA 2024

作者： Cao, Yi Xiao, Zonglin Qiao, Yuming School of Mechanical and Power Engineering Shenyang University of Chemical Technology 110142 China Department of Engineering Physics Tsinghua University Beijing100084 China

ISBN: (纸本)9781510682528

Real image editing has been one of the important research topics in the field of image generation, with the proposal of diffusion model, real image editing based on the guided diffusion model has become the mainstream, which edits the original real image through different conditions (text, image, sketch et al.), and outputs the edited image that align well with input conditions. Among them, the image-based real image editing task often can only migrate the style of the reference image to the original image, which is not controllable enough and lacks the ability of fine-grained image translation. In this paper, we propose I2IP, which introduces text prompt in the image translation process to control the image translation process in a fine-grained way, to improve the generalization and refinement of the image translation algorithm. Compared to text-based real image editing, I2IP can achieve image style transfer with reference image, while compared to image-based real image editing, I2IP takes the advantage of text-based image editing and control the editing result. © 2024 SPIE.

关键词： Image processing Diffusion Image restoration Semantics Image segmentation Process control reconstruction algorithms

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