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MAXIMUM-LIKELIHOOD IMAGE AND BLUR IDENTIFICATION - A UNIFYING APPROACH

OPTICAL ENGINEERING 1990年第5期29卷 422-435页

作者： LAGENDIJK, RL TEKALP, AM BIEMOND, J DELFT UNIV TECHNOL DEPT ELECT ENGNINFORMAT THEORY LAB2600 GA DELFTNETHERLANDS UNIV ROCHESTER DEPT ELECT ENGNROCHESTERNY 14627

Abstract not available

关键词： Point spread functions expectation maximization algorithms Signal to noise ratio Autoregressive models Filtering (signal processing) Image restoration Convolution Optimization (mathematics) Data modeling Image analysis

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The Effectiveness of a Probabilistic Principal Component Analysis Model and expectation Maximisation Algorithm in Treating Missing Daily Rainfall Data

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ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES 2020年第1期56卷 119-129页

作者： Chuan, Zun Liang Deni, Sayang Mohd Fam, Soo-Fen Ismail, Noriszura Univ Malaysia Pahang Fac Ind Sci & Technol Gambang Kuantan 26300 Pahang Dm Malaysia Univ Teknol MARA Fac Comp & Math Sci UiTM Shah Alam 40450 Malaysia Univ Tekn Malaysia Melaka Fac Technol Management & Technoprenetuship Durian Tunggal 76100 Melaka Malaysia Univ Kebangsaan Malaysia Fac Sci & Technol Sch Math Sci Bangi 43600 Selangor De Malaysia

The reliability and accuracy of a risk assessment of extreme hydro-meteorological events are highly dependent on the quality of the historical rainfall time series data. However, missing data in a time series such as this could result in lower quality data. Therefore, this paper proposes a multiple-imputation algorithm for treating missing data without requiring information from adjoining monitoring stations. The proposed imputation algorithms are based on the M-component probabilistic principal component analysis model and an expectation maximisation algorithm (MPPCA-EM). In order to evaluate the effectiveness of the MPPCA-EM imputation algorithm, six distinct historical daily rainfall time series data were recorded from six monitoring stations. These stations were located at the coastal and inland regions of the East-Coast Economic Region (ECER) Malaysia. The results of analysis show that, when it comes to treating missing historical daily rainfall time series data recorded from coastal monitoring stations, the 2-component probabilistic principal component analysis model and expectation-maximisation algorithm (2PPCA-EM) were found to be superior to the single- and multiple-imputation algorithms proposed in previous studies. On the contrary, the single-imputation algorithms as proposed in previous studies were superior to the MPPCA-EM imputation algorithms when treating missing historical daily rainfall time series data recorded from inland monitoring stations.

关键词： expectation maximization algorithms Missing daily rainfall Probabilistic principal component analysis model VIKOR technique

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A Generative Model for Segmentation of Tumor and Organs-at-Risk for Radiation Therapy Planning of Glioblastoma Patients

A Generative Model for Segmentation of Tumor and Organs-at-R...

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Conference on Medical Imaging - Image Processing

作者： Agn, Mikael Law, Ian af Rosenscold, Per Munck Van Leemput, Koen Tech Univ Denmark Dept Appl Math & Comp Sci Lyngby Denmark Copenhagen Univ Hosp Rigshosp Dept Clin Physiol Nucl Med & PET Copenhagen Denmark Copenhagen Univ Hosp Rigshosp Dept Oncol Copenhagen Denmark Harvard Med Sch MGH Martinos Ctr Biomed Imaging Boston MA USA

ISBN: (纸本)9781510600195

We present a fully automated generative method for simultaneous brain tumor and organs-at-risk segmentation in multi-modal magnetic resonance images. The method combines an existing whole-brain segmentation technique with a spatial tumor prior, which uses convolutional restricted Boltzmann machines to model tumor shape. The method is not tuned to any specific imaging protocol and can simultaneously segment the gross tumor volume, peritumoral edema and healthy tissue structures relevant for radiotherapy planning. We validate the method on a manually delineated clinical data set of glioblastoma patients by comparing segmentations of gross tumor volume, brainstemn and hippocampus. The preliminary results demonstrate the feasibility of the method.

关键词： Tumors Image segmentation Brain Tissues Radiotherapy Computed tomography Data modeling expectation maximization algorithms Electroluminescent displays Brain cancer Image analysis Magnetic resonance imaging Performance modeling Scanners

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EM scattering from a 2-D target above a 1-D sea surface using GPU based FDTD 4

EM scattering from a 2-D target above a 1-D sea surface usin...

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Conference on High-Performance Computing in Remote Sensing IV

作者： Guo, Lixin Jia, Chungang Yang, Pengju Xidian Univ Sch Phys & Optoelectron Engn Xian Peoples R China

ISBN: (纸本)9781628413106

This paper presents the graphics processor unit (GPU)-based finite difference time domain (FDTD) algorithm to investigate the electromagnetic (EM) scattering from a two-dimensional target above a one-dimensional rough sea surface with the Pierson-Moskowitz spectrum. The proposed method is validated by comparing the numerical results with those obtained through sequential FDTD execution on a central processing unit, as well as through method of moments. Using compute unified device architecture technology, significant speed-up ratios are achieved. Furthermore, the speedup is improved by shared memory and asynchronous transfer.

关键词： Finite-difference time-domain method Scattering Magnetism Composites expectation maximization algorithms Near field Electromagnetic scattering Detection and tracking algorithms Electromagnetism Visualization

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Joint PN code acquisition and DOA estimation technique for asynchronous DS-CDMA with antenna arrays

Joint PN code acquisition and DOA estimation technique for a...

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Conference on Digital Wireless Communications V

作者： Chuang, CY Kuo, CCJ Univ So Calif Dept Elect Engn Los Angeles CA 90089 USA

ISBN: (纸本)0819449601

Ail array processing approach to joint PN (pseudo-noise) code acquisition and DOA (direction-of-arrival) estimation in asynchronous direct-sequence code-division multiple access (DS-CDMA) systems is proposed. This problem is traditionally treated as a 2-D search problem in the space-time domain. Our approach transforms the 2-D space-time matrix data from the antenna output to several time domain vectors using a set of beams steering to different directions. Then, the acquisition process searches from these 1-D temporal vectors to provide soft information for the next stage, i.e. DOA estimation. Our algorithm is a blind approach, where the training sequence is not needed. Besides, the number of antennas required can be much less than that of the incoming signals, and the DOA search range can be largely reduced based on the soft information from the acquisition process. Numerical simulations are presented to demonstrate that the proposed solution is resistant to the near-far effect and robust to the change of the fading environment.

关键词： Antennas Spatial filters Signal processing Error analysis expectation maximization algorithms Computer simulations Statistical analysis Binary data Telecommunications Code division multiplexing

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Fast approach to evaluate MAP reconstruction for lesion detection and localization

Fast approach to evaluate MAP reconstruction for lesion dete...

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Medical Imaging 2004 Conference

作者： Qi, JY Huesman, RH Univ Calif Berkeley Lawrence Berkeley Lab Berkeley CA 94720 USA

ISBN: (纸本)0819452858

Lesion detection is an important task in emission tomography. Localization ROC (LROC) studies are often used to analyze the lesion detection and localization performance. Most researchers rely on Monte Carlo reconstruction samples to obtain LROC curves, which can be very time-consuming for iterative algorithms. In this paper we develop a fast approach to obtain LROC curves that does not require Monte Carlo reconstructions. We use a channelized Hotelling observer model to search for lesions, and the results can be easily extended to other numerical observers. We theoretically analyzed the mean and covariance of the observer output. Assuming the observer outputs are multivariate Gaussian random variables, an LROC curve can be directly generated by integrating the conditional probability density functions. The high-dimensional integrals are calculated using a Monte Carlo method. The proposed approach is very fast because no iterative reconstruction is involved. Computer simulations show that the results of the proposed method match well with those obtained using the tradition LROC analysis.

关键词： Monte Carlo methods Reconstruction algorithms Tolerancing Computer simulations Data modeling Convolution Positron emission tomography Tomography expectation maximization algorithms Analytical research

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High-resolution radar ranging for multiple targets

High-resolution radar ranging for multiple targets

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14th Conference on Signal and Data Processing of Small Targets

作者： Wang, Z Willett, P Bar-Shalom, Y Blair, WD Univ Connecticut Storrs CT 06269 USA

ISBN: (纸本)0819444782

The similarity between the multiple-target radar ranging problem and the multi-user detection problem in CDMA is drawn: in CDMA, users' bits modulate distinct but correlated signature signals;while, in radar, the "bits" are range-bin occupancies and the "signatures" correspond to the known transmitted signal translated to be centered on the appropriate range bin. The analogy is useful: there has been a great deal of recent experience in CDMA, and one of the best and fastest algorithms uses a variant of probabilistic data association (PDA, the target-tracking philosopk). PDA can be augmented by group decision feedback (GDF) - another idea from CDMA - to refine the target delay- estimates;and finally minimum description length (MDL) is applied to estimate the munber of targets. Simulation examples are given to illustrate the resolution of closely-spaced targets within what would normally- be thought the same range bin. Its performance is also compared with the Cramer-Rao lower bound (CRLB) and the alternating projection (AP) algorithm.

关键词： Personal digital assistants Radar Detection and tracking algorithms Target detection expectation maximization algorithms Signal detection Signal to noise ratio Ranging Correlation function Modulation

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Ultra-thin multiple-channel LWIR imaging systems

Ultra-thin multiple-channel LWIR imaging systems

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Conference on Infrared and Photoelectronic Imagers and Detector Devices

作者： Shankar, M. Willett, R. Pitsianis, N. P. Kolste, R. Te Chen, C. Gibbons, R. Brady, D. J. Duke Univ Fitzpatrick Inst Photon Durham NC 27708 USA Digital Opt Corp Charlotte NC 28262 USA Univ Delaware Newark DE 19716 USA Raytheon Co Mc Kinney TX 75071 USA

ISBN: (纸本)0819463736

Infrared camera systems may be made dramatically smaller by simultaneously collecting several low-resolution images with multiple narrow aperture lenses rather than collecting a single high-resolution image with one wide aperture lens. Conventional imaging systems consist of one or more optical elements that image a scene on the focal plane. The resolution depends on the wavelength of operation and the f-number of the lens system, assuming a diffraction limited operation. An image of comparable resolution may be obtained by using a multi-channel camera that collects multiple low-resolution measurements of the scene and then reconstructing a high-resolution image. The proposed infrared sensing system uses a three-by-three lenslet array with an effective focal length of 1.9mm. and overall system length of 2.3mm, and we achieve image resolution comparable to a conventional single lens system having a focal length of 5.7mm and overall system length of 26mm. The high-resolution final image generated by this system is reconstructed from the noisy low-resolution images corresponding to each lenslet;this is accomplished using a computational process known as superresolution reconstruction. The novelty of our approach to the superresolution problem is the use of wavelets and related multiresolution method within a expectation-maximization framework to improve the accuracy and visual quality of the reconstructed image. The wavelet-based regularization reduces the appearance of artifacts while preserving key features such as edges and singularities. The processing method is very fast, making the integrated sensing and processing viable for both time-sensitive applications and massive collections of sensor outputs.

关键词： Imaging systems Cameras Super resolution Infrared cameras Image processing expectation maximization algorithms Image resolution Sensors Long wavelength infrared Microlens array

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Community detection for fluorescent lifetime microscopy image segmentation

Community detection for fluorescent lifetime microscopy imag...

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Conference on Three-Dimensional and Multidimensional Microscopy - Image Acquisition and Processing XXI

作者： Hu, Dandan Sarder, Pinaki Ronhovde, Peter Achilefu, Samuel Nussinov, Zohar Washington Univ Dept Phys One Brookings DrCampus Box 1105 St Louis MO 63130 USA Washington Univ Sch Med Dept Radiol St Louis MO 63110 USA

ISBN: (纸本)9780819498625

Multiresolution community detection (CD) method has been suggested in a recent work as an efficient method for performing unsupervised segmentation of fluorescence lifetime (FLT) images of live cell images containing fluorescent molecular probes. 1 In the current paper, we further explore this method in FLT images of e x vivo tissue slices. The image processing problem is framed as identifying clusters with respective average FLTs against a background or "solvent" in FLT imaging microscopy (FLIM) images derived using NIR fluorescent dyes. We have identified significant multiresolution structures using replica correlations in these images, where such correlations are manifested by information theoretic overlaps of the independent solutions ("replicas") attained using the multiresolution CD method from different starting points. In this paper, our method is found to be more efficient than a current state-of-the-art image segmentation method based on mixture of Gaussian distributions. It offers more than 1 : 25 times diversity based on Shannon index than the latter method, in selecting clusters with distinct average FLTs in NIR FLIM images.

关键词： Image segmentation Fluorescence lifetime imaging Near infrared 3D image processing Critical dimension metrology expectation maximization algorithms Microscopy Image processing algorithms and systems Tissues Image resolution

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Novel time delay estimation methods with applications to ultra wideband ground penetrating radar

Novel time delay estimation methods with applications to ult...

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Radar Sensor Technology III

作者： Wu, RB Li, J Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA

ISBN: (纸本)0819428442

In this paper, we first present a Weighted Fourier transform and RELAXation based method (referred to as WRELAX), which is both computationally and statistically efficient, for the well-known time delay estimation problem. Later WRELAX is extended to multiple look cases where the receiver noise is assumed to be zero-mean colored Gaussian noise with unknown covariance matrices. Numerical examples show that;both WRELAX and its extensions can approach the corresponding Cramer-Rao bound, the minimum attainable variances for any unbiased estimators, for a wide range of signal-to-noise ratios. The new algorithm can be applied to detecting and classifying roadway subsurface anomalies by using an ultra wideband ground penetrating radar. Experimental examples are also provided to demonstrate the performance of the new algorithm.

关键词： Evolutionary algorithms Ground penetrating radar Signal to noise ratio Fourier transforms expectation maximization algorithms Optimization (mathematics) Radar Electronic filtering Receivers Statistical analysis

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