• Title/Summary/Keyword: maximum a posteriori

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Three-Dimensional Image Reconstruction from Compton Scattered Data Using the Row-Action Maximum Likelihood Algorithm (행작용 최대우도 알고리즘을 사용한 컴프턴 산란 데이터로부터의 3차원 영상재구성)

  • Lee, Mi-No;Lee, Soo-Jin;Nguyen, Van-Giang;Kim, Soo-Mee;Lee, Jae-Sung
    • Journal of Biomedical Engineering Research
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    • v.30 no.1
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    • pp.56-65
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    • 2009
  • Compton imaging is often recognized as a potentially more valuable 3-D technique in nuclear medicine than conventional emission tomography. Due to inherent computational limitations, however, it has been of a difficult problem to reconstruct images with good accuracy. In this work we show that the row-action maximum likelihood algorithm (RAMLA), which have proven useful for conventional tomographic reconstruction, can also be applied to the problem of 3-D reconstruction of cone-beam projections from Compton scattered data. The major advantage of RAMLA is that it converges to a true maximum likelihood solution at an order of magnitude faster than the standard expectation maximiation (EM) algorithm. For our simulations, we first model a Compton camera system consisting of the three pairs of scatterer and absorber detectors placed at x-, y- and z-axes, and generate conical projection data using a software phantom. We then compare the quantitative performance of RAMLA and EM reconstructions in terms of the percentage error. The net conclusion based on our experimental results is that the RAMLA applied to Compton camera reconstruction significantly outperforms the EM algorithm in convergence rate; while computational costs of one iteration of RAMLA and EM are about the same, one iteration of RAMLA performs as well as 128 iterations of EM.

Low-Complexity Robust ML Signal Detection for Generalized Spatial Modulation (일반화 공간변조를 위한 저복잡도 강인 최대 우도 신호 검파)

  • Kim, Jeong-Han;Yoon, Tae-Seon;Oh, Se-Hoon;Lee, Kyungchun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.3
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    • pp.516-522
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    • 2017
  • In this paper, we propose a maximum likelihood signal detection scheme for a generalized spatial modulation system that activates only a subset of transmit antennas among multiple antennas and transmits information through the indexes of active antennas as well as through the transmit symbols. The proposed maximum likelihood receiver extracts a set of candidate solutions based on their a posteriori probabilities to lower the computational load of the robust receiver under channel information errors. Then, the chosen candidate solutions are exploited to estimate the covariance matrix of effective noise. Simulation results show that the proposed maximum likelihood detection scheme achieves better error performance than a receiver that does not take into account the channel information errors. It is also seen that it reduces the computational complexity with the same bit error rate performance as the conventional robust maximum likelihood receiver.

Ordinal Measure of DCT Coefficients for Image Correspondence and Its Application to Copy Detection

  • Changick Kim
    • Journal of Broadcast Engineering
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    • v.7 no.2
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    • pp.168-180
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    • 2002
  • This paper proposes a novel method to detect unauthorized copies of digital images. This copy detection scheme can be used as either an alternative approach or a complementary approach to watermarking. A test image is reduced to 8$\times$8 sub-image by intensity averaging, and the AC coefficients of its discrete cosine transform (DCT) are used to compute distance from those generated from the query image, of which a user wants to find copies. Copies may be Processed to avoid copy detection or enhance image quality. We show ordinal measure of DCT coefficients, which is based on relative ordering of AC magnitude values and using distance metrics between two rank permutations, are robust to various modifications of the original image. The optimal threshold selection scheme using the maximum a posteriori (MAP) criterion is also addressed.

An Image Synthesis Technique Based on the Pyramidal Structure and MAP Estimation Technique (계층적 Pyramid구조와 MAP 추정 기법을 이용한 Texture 영상 합성 기법)

  • 정석윤;이상욱
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.26 no.8
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    • pp.1238-1246
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    • 1989
  • In this paper, a texture synthesis technique based on the NCAR(non-causal auto-regressive) model and the pyramid structure is proposed. In order to estimate the NCAR model parameters accurately from a noisy texture, the MAP(maximum a posteriori) estimation technique is also employed. In our approach, since the input texture is decomposed into the Laplacian oyramid planes first and then the NCAR model is applied to each plane, we are able to obtain a good synthesized texture even if the texture exhibits some non-random local structure or non-homogenity. The usrfulness of the proposed method is demonstrated with seveal real textures in the Brodatz album. Finally, the 2-dimensional MAP estimation technique can be used to the image restoration for noisy images as well as a texture image synthesis.

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QRS detection based on maximum a-posteriori estimation (MAP Estimation을 이용한 QRS Detection)

  • 정희교;신건수;이명호
    • 제어로봇시스템학회:학술대회논문집
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    • 1987.10b
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    • pp.709-712
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    • 1987
  • In this paper, a mathematical model for the purpose of QRS detection is considered in the case of the occurrence of nonoverlapping pulse-shaped waveforms corrupted with white noise. The number of waveforms, the arrival times, amplitudes, and widths of QRS complexes are regarded as random variables. The joint MAP estimation of all the unknown quantities consists of linear filtering followed by an optimization procedure. Because of time-consuming, the optimization procedure is modified so that a threshold test is obtained. The model formulation with nonoverlapping waveforms leads to a standard procedure covering a segment before as well as after an accepted event. Adaptivity of the detector is gained by utilizing past signal properties in determining threshold for QRS detection.

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Statistical Model-Based Voice Activity Detection Based on Second-Order Conditional MAP with Soft Decision

  • Chang, Joon-Hyuk
    • ETRI Journal
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    • v.34 no.2
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    • pp.184-189
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    • 2012
  • In this paper, we propose a novel approach to statistical model-based voice activity detection (VAD) that incorporates a second-order conditional maximum a posteriori (CMAP) criterion. As a technical improvement for the first-order CMAP criterion in [1], we consider both the current observation and the voice activity decision in the previous two frames to take full consideration of the interframe correlation of voice activity. This is clearly different from the previous approach [1] in that we employ the voice activity decisions in the second-order (previous two frames) CMAP, which has quadruple thresholds with an additional degree of freedom, rather than the first-order (previous single frame). Also, a soft-decision scheme is incorporated, resulting in time-varying thresholds for further performance improvement. Experimental results show that the proposed algorithm outperforms the conventional CMAP-based VAD technique under various experimental conditions.

Multilayer Stereo Image Matching Based upon Phase-Magnitude an Mean Field Approximation

  • Hong Jeong;Kim, Jung-Gu;Chae, Myoung-Sik
    • Journal of Electrical Engineering and information Science
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    • v.2 no.5
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    • pp.79-88
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    • 1997
  • This paper introduces a new energy function, as maximum a posteriori(MAP) estimate of binocular disparity, that can deal with both random dot stereo-gram(RDS) and natural scenes. The energy function uses phase-magnitude as features to detect only the shift for a pair of corrupted conjugate images. Also we adopted Fleet singularity that effectively detects unstable areas of image plant and thus eliminates in advance error-prone stereo mathcing. The multi-scale concept is applied to the multi laser architecture that can search the solutions systematically from coarse to fine details and thereby avoids drastically the local minima. Using mean field approximation, we obtained a compact representation that is suitable for fast computation. In this manner, the energy function satisfies major natural constraints and requirements for implementing parallel relaxation. As an experiment, the proposed algorithm is applied to RDS and natural stereo images. As a result we will see that it reveals good performance in terms of recognition errors, parallel implementation, and noise characteristics.

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Throughput Improvement of Adaptive Modulation System with an Efficient Turbo-Coded V-BLAST Technique in each MIMO Channel

  • Ryoo, Sang-Jin;Kim, Seo-Gyun;Na, Cheol-Hun;Hong, Jin-Woo;Hwang, In-Tae
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.05a
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    • pp.905-908
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    • 2008
  • In this paper, an Adaptive Modulation (AM) system with an efficient turbo-coded Vertical-Bell-lab Layered Space-Time (V-BLAST) technique is proposed. The proposed decoding algorithm adopts iteratively the extrinsic information from a Maximum a Posteriori (MAP) decoder as a priori probability in the two decoding procedures of the V-BLAST scheme of ordering and slicing. In this analysis, each MIMO channel is assumed to be a part of the system of performance improvement.

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Error Performance of Serially Concatenated Space-Time Coding

  • Altunbas, Ibrahim;Yongacoglu, Abbas
    • Journal of Communications and Networks
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    • v.5 no.2
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    • pp.135-140
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    • 2003
  • In this paper, we investigate the error performance of a serially concatenated system using a nonrecursive convolutional code as the outer code and a recursive QPSK space-time trellis code as the inner code on quasi-static and rapid Rayleigh fading channels. At the receiver, we consider iterative decoding based on the maximum a posteriori (MAP) algorithm. The performance is evaluated by means of computer simulations and it is shown that better error performance can be obtained by using low complexity outer and/or inner codes and the Euclidean distance criterion based recursive space-time inner codes. We also obtain new systems with large number of trasmit and/or receive antennas providing good error performance.

Adaptive Noise Reduction Algorithm for an Image Based on a Bayesian Method

  • Kim, Yeong-Hwa;Nam, Ji-Ho
    • Communications for Statistical Applications and Methods
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    • v.19 no.4
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    • pp.619-628
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    • 2012
  • Noise reduction is an important issue in the field of image processing because image noise lowers the quality of the original pure image. The basic difficulty is that the noise and the signal are not easily distinguished. Simple smoothing is the most basic and important procedure to effectively remove the noise; however, the weakness is that the feature area is simultaneously blurred. In this research, we use ways to measure the degree of noise with respect to the degree of image features and propose a Bayesian noise reduction method based on MAP (maximum a posteriori). Simulation results show that the proposed adaptive noise reduction algorithm using Bayesian MAP provides good performance regardless of the level of noise variance.