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37th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Liu, Jing He, Qiong Luo, Jianwen Tsinghua Univ Dept Biomed Engn Beijing 100084 Peoples R China Tsinghua Univ Ctr Biomed Imaging Res Beijing 100084 Peoples R China

ISBN: (纸本)9781424492701

Compressed sensing (CS) or compressive sampling allows much lower sampling frequency than the Nyquist sampling frequency. In this paper, we propose a novel technique, named compressed sensing based synthetic transmit aperture (CS-STA), to speed up the acquisition of ultrasound imaging. Ultrasound transducer transmits plane wave with random apodizations for several times and receives the corresponding echoes. The full dataset of STA is then recovered from the recorded echoes using a CS reconstruction algorithm. Finally, a standard STA beamforming is performed on the dataset to form a B-mode image. When the number of CS-STA firings is smaller than the number of STA firings, higher frame rate is achieved. In addition, CS-STA maintains the high resolution of STA because of the CS recovered full dataset of STA, and improves the contrast due to plane wave firings. Computer simulations and phantom experiments are carried out to investigate the feasibility and performance of the proposed CS-STA method. The CS-STA method is proven to be capable of obtaining simultaneously high frame rate, high solution and high contrast ultrasound imaging.

关键词： CS STA High Frame Rate stormwater treatment areas Frame Rate carbon monosulfide CONTAINMENT SPRAY Cesium Compressed sensing Ultrasonography High definition FIRING ultrasonic transducers Dataset conditioned stimulus reconstruction algorithm high-contrast

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DEM Construction and Calibration of Hyperspectral Image Data Using Pairs of Radiance Images

DEM Construction and Calibration of Hyperspectral Image Data...

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7th International Symposium on Image and Signal Processing and Analysis (ISPA)

作者： Grumpe, Arne M. Woehler, Christian TU Dortmund Fac Elect Engn & Informat Technol Image Anal Grp Otto Hahn Str 4 D-44227 Dortmund Germany

ISBN: (纸本)9789531841597

In lunar remote sensing, the analysis of the spectral reflectance of iron-bearing minerals is a widely used method. For an accurate calibration, elevation information about the surface has to be known. In this paper we present a framework for the reconstruction of digital elevation maps (DEM) from hyperspectral imagery and preexisting elevation data of lower lateral resolution. The reconstruction algorithm consists of a combined photoclinometry and shape from shading scheme, which is extended towards photometric stereo using multiple images. In order to register images of the same surface region acquired under different illumination conditions, an image registration approach is derived from the DEM construction methods. Image registration is performed in the illumination-invariant surface gradient space and is therefore able to cope with images taken under different illumination conditions. Finally, the calibration of hyperspectral imagery based on the DEM is demonstrated by the analysis of extracted spectral features.

关键词： hyperspectral imagery image data images multiple image reconstruction algorithm Region of surface spectral reflectance image registration radiance Calibration Lighting illumination

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Binary 3D-Matrices Under the Microscope: A Tomographical Problem

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Electronic Notes in Discrete Mathematics 2005年 20卷 573-586页

作者： Masilamani, V. Dersanambika, K.S. Krithivasan, K. Department of Computer Science and Engineering Indian Institute of Technology Madras Chennai 600 036 India

A binary 3D-matrix can be scanned by moving a fixed 3D-window across it. We define scan matrix based on this and define smooth matrix. We present algorithm to reconstruct the original matrix from its 3D-scan matrix in... 详细信息

关键词： 3D-scan matrix reconstruction algorithm smooth matrix

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Localization from Connectivity: 1-Bit Maximum Likelihood Approach

Localization from Connectivity: 1-Bit Maximum Likelihood App...

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Bhaskar, Sonia A. Stanford Univ Dept Elect Engn Stanford CA 94304 USA

ISBN: (纸本)9781479984060

We consider the problem of determining the location of sensor nodes in a wireless sensor ad hoc network when only connectivity information is available, i.e., one only knows if a pair of nodes are within a fixed radio range (distance) of each other but does not have access to exact or even approximate distance information. We propose a maximum likelihood based reconstruction algorithm to reconstruct the node positions in a.. dimensional Euclidean space. The original problem formulation results in constrained minimization of a negative log-likelihood with respect to n x n symmetric positive semidefinite matrices Q for an n-node network, and is a convex optimization problem. We recast this problem into a non-convex optimization problem with respect to X where Q = (XX)-X-inverted perpendicular We link our algorithm to existing results which confirm that the nonconvex optimization problem with m x n X provides a global solution to its convex equivalent for certain choices of m. We demonstrate that our algorithm is empirically successful for both uniform and irregular networks, using only a few anchor nodes. Finally, numerical experiments demonstrate improved performance of the proposed algorithm relative to the MDS algorithm and a variant.

关键词： maximum likelihood 1-bit Ganglia network node reconstruction algorithm Euclidean space Convex function algorithms Quality factor

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Non-Uniform Sampling schemes for IF Sampling radio receiver

Non-Uniform Sampling schemes for IF Sampling radio receiver

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International Conference on Design and Test of Integrated Systems in Nanoscale Technology

作者： Ben-Romdhane, Manel Rebai, Chiheb Ghazel, Adel Desgeys, Patricia Loumeau, Patrick SUPCOM CIRTACOM Res Unit Tunis Tunisia TELECOM LTCI CNRS UMR F-5141 Paris France

ISBN: (纸本)0780397266

The IF Sampling radio receiver based on the Non-Uniform Sampling NUS Technique is promising and would be a candidate for the multistandard reception. This technique allows the IF down-conversion and permit to eliminate or alleviate the anti-aliasing filter. For wideband and multistandards design, the choice of sampling rates for bandpass sampling is flexible. This paper introduces the NUS theory' particularly its random processes schemes;the Additive Random Sampling ARS and the Jittered Random Sampling JRS. Then, it proposes the IF NUS receiver architecture. The reconstruction algorithm RA block represents the object of the comparison between the sampling schemes. Finally, validation of the algorithm, its anti-aliasing specificity and some simulation results are presented.

关键词： Non-Uniform Sampling band-pass sampling radio receiver anti-aliasing reconstruction algorithm signal-to-noise ratio

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Investigation of microwave tomographic imaging techniques for industrial processes

Investigation of microwave tomographic imaging techniques fo...

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Conference on Process Imaging for Automatic Control

作者： Wu, Z Boughriet, A McCann, H Davis, LE Nugroho, AT Univ Manchester Inst Sci & Technol Dept Elect Engn & Elect Manchester M60 1QD Lancs England

ISBN: (纸本)0819438537

Microwave tomographic imaging techniques have mainly been studied for medical applications in the past two decades. In recent years, however, there has been increased interest in the application of microwave imaging techniques for industrial processes or multiphase flows. In the medical case, water has been used as the background material, with microwave antennas and the object immersed in water, and the contrast of the object is measured against the dielectric properties of water. For industrial application, it is more convenient to use air as the background medium. However, this leads to a large contrast problem if the material being imaged contains a large amount of water. Consequently, the image reconstruction algorithms need to be more adaptive to the level of contrast and uncertainty in the initial guessed values in the iterative reconstruction process. The electromagnetic noise in the open air environment would usually be higher than that in water as a result of the surrounding industrial noise, and the near field region is much larger in air than that in water at the same operating frequency. Therefore, the algorithms need to be less sensitive to the effect of noise. In this paper, two algorithms based on the Newton-Kantorovich and Conjugate Gradient error minimisation methods are investigated with a view to their applications in the imaging of industrial processes using air as the background medium. The results on the effect of noise and the images reconstructed using the algorithms are presented.

关键词： microwave tomographic imaging reconstruction algorithm process

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algorithms for Wavelet Decomposition of of the Space of Hermite Type Splines

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Journal of Mathematical Sciences (United States) 2019年第1期242卷 133-148页

作者： Dem’yanovich, Yu. K. St. Petersburg State University 28 Universitetskii pr. Petrodvorets St. Petersburg 198504 Russian Federation

For the space of (not necessarily polynomial) Hermite type splines we develop algorithms for constructing the spline-wavelet decomposition provided that an arbitrary coarsening of a nonuniform spline-grid is a priori given. The construction is based on approximate relations guaranteeing the asymptotically optimal (with respect to the N-diameter of standard compact sets) approximate properties of this decomposition. We study the structure of restriction and extension matrices and prove that each of these matrices is the one-sided inverse of the transposed other. We propose the decomposition and reconstruction algorithms consisting of a small number of arithmetical actions. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

关键词： SGCG gene decomposition algorithms matrices splines (mathematics) reconstruction algorithm

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A New Secret Image Sharing Scheme Based on Compressed Sensing 2

A New Secret Image Sharing Scheme Based on Compressed Sensin...

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2nd IEEE International Conference on Cloud Computing and Big Data Analysis (ICCCBDA)

作者： Yang, Fuqiang Dang, Na Zhang, Junxing Inner Mongolia Univ Sch Comp Sci Hohhot Peoples R China

ISBN: (纸本)9781509044993

In traditional secret image sharing schemes, all the data of a secret image have to be processed, which prolongs the algorithm execution. Meanwhile, the inflated data become a burden for network transmission and disk storage when many secret images need to be routinely shared. Compressed sensing technology measures the original image perceptually through a proper measurement matrix, and the measured data cover the vast majority of the useful information of the original image. While ensuring precise reconstruction, the original image is compressed from high dimensional to low dimensional and the amount of image data decreases dramatically. Thus, a number of problems caused by the large amount of data in traditional secret image sharing schemes could be solved by compressed sensing. In this paper, we combine the traditional secret image sharing with compressed sensing technology and show through experiments that the proposed method can clearly reduce the amount of data need to be processed and effectively shorten the algorithm execution time. The experimental results reveal that our method can shorten the image sharing time by 2.7% to 57.3% and the image restoration time by 3.3% to 57.7% under different compression ratios.

关键词： secret image sharing compressed sensing reconstruction algorithm

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reconstruction of atomic measures from their halfspace depth

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JOURNAL OF MULTIVARIATE ANALYSIS 2021年 183卷 104727-104727页

作者： Laketa, Petra Nagy, Stanislav Charles Univ Prague Dept Probabil & Math Stat Fac Math & Phys Sokolovska 83 Prague 18675 8 Czech Republic

The halfspace depth can be seen as a mapping that to a finite Borel measure mu on the Euclidean space R-d assigns its depth, being a function R-d -> [0, infinity): x -> D (x;mu). The depth of mu quantifies how much centrally positioned a point x is with respect to mu. This function is intended to serve as generalization of the quantile function to multivariate spaces. We consider the problem of finding the inverse mapping to the halfspace depth: knowing only the function x -> D (x;mu), our objective is to reconstruct the measure mu. We focus on mu atomic with finitely many atoms, and present a simple method for the reconstruction of the position and the weights of all atoms of mu, from its depth only. As a consequence, (i) we recover generalizations of several related results known from the literature, with substantially simplified proofs, and (ii) design a novel reconstruction procedure that is numerically more stable, and considerably faster than the known algorithms. Our analysis presents a comprehensive treatment of the halfspace depth of those measures whose depths attain finitely many different values. (C) 2021 Elsevier Inc. All rights reserved.

关键词： Atomic measure Depth contour Halfspace depth reconstruction algorithm Tukey depth

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Compressed sensing photoacoustic imaging for high-speed imaging with sparse measurement: a theoretical study

Compressed sensing photoacoustic imaging for high-speed imag...

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Conference on Computational Optics Held as Part of Part of SPIE Optical Systems Design Conference

作者： Tang, Jiaqi Zhao, Aojie Li, Bo Song, Xianlin Nanchang Univ Sch Informat Engn Nanchang 330031 Jiangxi Peoples R China

ISBN: (数字)9781510645950

ISBN: (纸本)9781510645950;9781510645943

As a new non-destructive medical imaging technology, photoacoustic imaging combines the advantages of optical imaging and ultrasonic imaging, which has the characteristics of high contrast and strong penetration ability. It can effectively image biological tissues and functions, and be applied to the early diagnosis and treatment of tumors, cardiovascular and cerebrovascular diseases, which has broad prospects for development in the field of biomedicine. When photoacoustic imaging is used to collect a large number of pathological medical images, it is prone to slow data transmission and poor reconstruction effect. In an effort to speed up data transmission and improve image reconstruction quality, this article is based on photoacoustic imaging technology and compressed sensing reconstruction algorithm, a virtual simulation platform of photoacoustic tomography combined with compressive sensing is built by using K-wave simulation toolbox, and the hard thresholding pursuit algorithm is used to complete the signal reconstruction. In order to verify the performance of the virtual simulation platform, in this paper, the local vascular network is compressed and reconstructed. The reconstructed image retains the main information of the original image, and the edge features are similar. The results show that the virtual simulation platform can reconstruct high quality images by a small amount of data, which provides important significance and theoretical research value for the application of the compressed sensing in photoacoustic imaging.

关键词： photoacoustic tomography K-wave simulation toolbox compressed sensing reconstruction algorithm hard thresholding pursuit

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