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IEEE Conference on Computer Vision and Pattern Recognition

作者： Kai Han Kwan-Yee K. Wong Miaomiao Liu The University of Hong Kong NICTA and CECS ANU

ISBN: (纸本)9781467369657

This paper addresses the problem of reconstructing the surface shape of transparent objects. The difficulty of this problem originates from the viewpoint dependent appearance of a transparent object, which quickly makes reconstruction methods tailored for diffuse surfaces fail disgrace-fully. In this paper, we develop a fixed viewpoint approach for dense surface reconstruction of transparent objects based on refraction of light. We introduce a simple setup that allows us alter the incident light paths before light rays enter the object, and develop a method for recovering the object surface based on reconstructing and triangulating such incident light paths. Our proposed approach does not need to model the complex interactions of light as it travels through the object, neither does it assume any parametric form for the shape of the object nor the exact number of refractions and reflections taken place along the light paths. It can therefore handle transparent objects with a complex shape and structure, with unknown and even inhomogeneous refractive index. Experimental results on both synthetic and real data are presented which demonstrate the feasibility and accuracy of our proposed approach.

关键词： Hyalin Light refractions Light refraction Comment reconstruction algorithm Surface reconstruction incident light Paths Reflection

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Fault Detection for Aircraft Control Surfaces Using Approximate Input reconstruction

Fault Detection for Aircraft Control Surfaces Using Approxim...

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2009 American Control Conference (ACC 2009)

作者： Haoyun Fu Jin Yan Mario A. Santillo Harish J. Palanthandalam-Madapusi Dennis S. Bernstein Department of Aerospace Engineering The University of Michigan Ann Arbor MI 48109 Department of Mechanical and Aerospace Engineering Syracuse University Syracuse NY 13244

ISBN: (纸本)9781424445233

We use an approximate input reconstruction algorithm to reconstruct unknown inputs, which are then used as a basis for fault detection. The approximate input reconstruction algorithm is a least squares algorithm that estimates both the unknown initial state and input history. The estimated inputs are then compared to the commanded values and sensor values to assess the health of actuators and sensors. This approach is applied to the longitudinal and lateral dynamics of an aircraft. The input reconstruction algorithm can be used for minimum-phase or nonminimum-phase zeros;however, zeros on the unit circle yield persistent estimation errors and thus poor input reconstruction.

关键词： Defect detection Unit circle reconstruction algorithm Aircraft control Error analysis Approximate actuators Zero Reconstructive Surgical Procedures ENTERING

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FOREGROUND AND BACKGROUND reconstruction IN POISSON VIDEO

FOREGROUND AND BACKGROUND RECONSTRUCTION IN POISSON VIDEO

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IEEE International Conference on Image Processing

作者： Eric C. Hall Rebecca M. Willett Department of Electrical and Computer Engineering Duke University NC 27708

ISBN: (纸本)9781479923427

Image foreground and background separation is an essential step in a variety of image processing, video analysis, and computer vision tasks. Typically, these methods accept streaming video data, compute an estimate of the background, and subtract this from the observed frames to generate a foreground scene. While such methods are very effective in high SNR regimes, they face serious limitations in low-light settings occurring in night vision surveillance and astronomy. Existing methods cannot be easily modified to yield good results. Therefore, new methods must be created to deal with the low light setting. This paper specifically addresses the problem of foreground and background separation and reconstruction in the case of Poisson distributed observations. The proposed approach builds upon recent advances in both the online learning community and sparse reconstruction methods for Poisson images. To aid in the reconstruction and separation tasks, the method learns and incorporates the dynamics of objects in both the background and foreground in real time.

关键词： Photon-limited imaging Background estimation Object tracking Online optimization Sim'eon Denis Poisson Videotapes tracking objects images reconstructions BACKGROUND reconstruction algorithm indium e-learning video data

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UNDERDETERMINED DOA ESTIMATION OF MULTI-PATH SIGNALS BASED ON ICA AND SPARSE reconstruction

UNDERDETERMINED DOA ESTIMATION OF MULTI-PATH SIGNALS BASED O...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Kunlai Xiong Zhangmeng Liu Zheng Liu Daowang Feng Wenli Jiang College of Electronic Science and Engineering National University of Defense Technology Changsha Hunan People's Republic of China

ISBN: (纸本)9781479928941

This paper proposes a method for estimating the direction of arrival (DOA) of multi-path signals for an underdetermined case, where the number of incident signals exceeds the number of sensors. Some DOA estimation methods have already been proposed for multi-path signals. However, most of them cannot be used for an underdetermined case. To deal with this problem, we propose a novel DOA estimation method which combines independent component analysis (ICA) and sparse reconstruction algorithm. It can estimate DOA of M × (M-1) incident signals when the number of sensors is M. The simulation results demonstrate the promising performance of the proposed algorithm compared to several state of the art methods.

关键词： Independent component analysis United States Department of Agriculture islet cell antibody state of the art Direction of arrival estimation signals multipath signal multi-path reconstruction algorithm Sensors

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Performance Evaluation of SAR Image reconstruction on CPUs and GPUs

Performance Evaluation of SAR Image Reconstruction on CPUs a...

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IEEE Aerospace Conference

作者： Fisnik Kraja Alin Murarasu Georg Acher Arndt Bode Chair of Computer Architecture Technische Universitat Munchen Munich Germany

ISBN: (纸本)9781457705564

Future space applications will demand for architectures with High Performance Computing (HPC) capabilities. In this scope, on-board computer designers will have to select between different technologies and designs, the most reliable and most efficient ones in terms of performance and power consumption. In this paper, we investigate the behavior of an Image reconstruction algorithm on high performance multi-core CPUs and many-core GPUs. It turns out that SAR applications can profit much more from the architecture and the capabilities of many-core GPUs than from modern multi-core CPUs. We give some remarks on how these types of HPC components can be integrated on future space-based on-board computing platforms. Throughout the paper, we illustrate by comparison the advantages and disadvantages of using GPUs over CPUs for SAR Applications. Other than this, we explain the programming and parallelization paradigms applied to the SAR application to increase its performance and efficiency on CPUs and GPUs respectively.

关键词： central processing units Rescue Synthetic aperture radar Specific absorption rate SAFETY ANALYSIS REPORTS Performance Evaluation High Performance Computing ARCHITECTURE image reconstruction reconstruction algorithm Space applications Building construction

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IMAGE reconstruction AND THRESHOLD DESIGN FOR QUANTA IMAGE SENSORS

IMAGE RECONSTRUCTION AND THRESHOLD DESIGN FOR QUANTA IMAGE S...

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IEEE International Conference on Image Processing

作者： Omar A. Elgendy Stanley H. Chan School of ECE and Dept of Statistics Purdue University

ISBN: (纸本)9781467399623

Quanta Image Sensor (QIS) has been envisioned as a candidate solution for next generation image sensors. We provide two new contributions to the signal processing aspects of QIS. First, we develop an image reconstruction algorithm to recover the underlying images from the QIS data, which is a massive array of binarized Poisson random variables. The new algorithm supersedes existing methods by enabling arbitrary threshold level. Second, we present a threshold design scheme to adaptively update the threshold level for optimal image reconstruction. We discuss the existence of a phase transition in determining the optimal threshold. Experimental results on tone-mapped high dynamic range images validates the effectiveness of the threshold scheme and the image reconstruction algorithm.

关键词： Image reconstruction Quanta image sensors ADMM High dynamic range Quantization map image reconstruction threshold level reconstruction algorithm HIGH DYNAMIC RANGE Feasible Solution images Sensors (image) Sensors Phase transtormations

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SIMULTANEOUS reconstruction OF UNDERSAMPLED MULTICHANNEL SIGNALS WITH A DECAYED AND TIME-DELAYED COMMON COMPONENT

SIMULTANEOUS RECONSTRUCTION OF UNDERSAMPLED MULTICHANNEL SIG...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Yoshifumi Shiraki Yutaka Kamamoto Takehiro Moriya NTT Communication Science Laboratories Nippon Telegraph and Telephone Corporation. 3-1 Morinosato-Wakamiya Atsugi Kanagawa 243-0198 Japan.

ISBN: (纸本)9781479903573

This paper presents a new signal model in distributed compressed sensing (DCS) and a reconstruction algorithm to reduce the number of samples required to accurately reconstruct signals obtained via sensors. While the conventional signal models in DCS assume that all signals include exactly the same common component, our model exploits the attenuation and time delay of the common component. With this extension, one can deal with signals originated from a source located in the field. To reconstruct such signals, we developed a new algorithm based on the alternative direction multiplier method. The algorithm efficiently reconstructs computer-generated signals using a reduced number of samples. In addition, we demonstrate the superior reconstruction quality with our method by using real electromyographic signals.

关键词： Distributed Compressed Sensing Sensor Network Alternative Direction Method signals reconstruction algorithm Sensor networks MULTICHANNEL reconstructions Concurrency time delay Random number sampling

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Compressed Sensing-based FH-BPSK Signals' Digital Domain Compressive Sampling and reconstruction

Compressed Sensing-based FH-BPSK Signals' Digital Domain Com...

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2016 IEEE 13th International Conference on Signal Processing（ICSP2016）

作者： Yidong Zhang Wenge Yang Yanhe Cheng Xinfeng Mao Shiqiang Sheng Department of Optical and Electrical Equipment Equipment Academy

In order to effectively solve the problem of dealing pressure in ultra wideband, ultra high frequency, high bit rate, and high sampling rate of frequency hopping signal in military satellite communications and aerospace TT& C communication system, the present paper focuses on the study of the digital domain compressive sampling and reconstruction algorithm of frequency hopping signal by taking the basic principles and methods of compressed sensing. It first discusses the compressive sampling model, FH-BPSK（frequency hopping binary phaseshiftkeying） modulation signal model and its sparsity. Then, it focuses on the RIP（Restricted Isometry Property） and incoherent properties of measurement matrix in digital domain compressive sampling, as well as noise folding caused by compressive sampling. After that, it compares the reconstruction algorithm of FH-BPSK signals of compressive sampling and sparsity. It also discusses the reconstruction algorithm and its improvement of SL（Smoothed L Norm） and compares it with the classical OMP（Orthogonal Matching Pursuit） algorithm. Finally, the simulative experiments illustrate the performance and conclusion, exploring the relationship among the SNR（Signal to Noise Ratio）, compression ratio, relative error and run time in the reconstruction of the FH-BPSK signal under certain conditions. The results show that provided the original information be retained, the digital sampling rate will drop significantly, providing new possibilities for subsequent compressed domain information processing.

关键词： compressed sensing reconstruction algorithm compressive sampling noise folding incoherent FH-BPSK signals

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Random sampling in multiply generated shift-invariant subspaces of mixed Lebesgue spaces L^p,q(R x R^d)

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JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2021年 386卷 113237-113237页

作者： Jiang, Yingchun Li, Wan Guilin Univ Elect Technol Sch Math & Computat Sci Guilin 541004 Peoples R China

We mainly study the random sampling and reconstruction in multiply generated shift-invariant subspaces V-p,V-q(Phi) of mixed Lebesgue spaces L-p,L-q(R x R-d). Under suitable conditions for the generators Phi, we can prove that if the sampling sizes are large enough for both variables, the sampling stability holds with high probability for all functions in V-p,V-q(Phi) whose energy is concentrated on a compact subset. Finally, a reconstruction algorithm based on random samples is given for functions in a finite dimensional subspace. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Random sampling Mixed Lebesgue space Shift-invariant subspace Sampling stability reconstruction algorithm

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The use of contrast for automated pulmonary nodule detection in low-dose computed tomography

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MEDICAL PHYSICS 1999年第3期26卷 427-437页

作者： Narayan, TK Herman, GT Univ Penn Dept Radiol Med Image Proc Grp Philadelphia PA 19104 USA

A methodology for automated detection of pulmonary nodules in low-dose computed tomography (CT) images is investigated. The methodology in question consists of (i) identifying some connected set of pixels in the CT image as a potential site for a nodule (this set of pixels is referred to as the target);(ii) specifying a further small set of pixels which are believed to be in the healthy tissue surrounding the target (this set of pixels is referred to as the background);and (iii) evaluating a function that is calculated based on the CT values in the target and in the background. The value of this function is indicative of the "noduleness" of the target;hence such a function is referred to as a detector. We present a large family of such detectors;two widely used detectors included in this family are contrast and signal-to-noise ratio (SNR). We show that for automated nodule detection contrast appears to be the detector of choice from this family (and, in particular, that contrast proves to be a detector superior to SNR for a variety of situations). Such claims are validated using a receiver operating characteristic (ROC) study on simulated low-dose CT data sets (representative of thoracic cross sections with nodules) and with reconstruction algorithms appropriately optimized for the purpose of automated nodule detection. (C) 1999 American Association of Physicists in Medicine. [S0094-2405(99)00603-3].

关键词： automated detection reconstruction algorithm low-dose CT pulmonary nodules

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