• Title/Summary/Keyword: Reconstruction error

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Penalized-Likelihood Image Reconstruction for Transmission Tomography Using Spline Regularizers (스플라인 정칙자를 사용한 투과 단층촬영을 위한 벌점우도 영상재구성)

  • Jung, J.E.;Lee, S.-J.
    • Journal of Biomedical Engineering Research
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    • v.36 no.5
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    • pp.211-220
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    • 2015
  • Recently, model-based iterative reconstruction (MBIR) has played an important role in transmission tomography by significantly improving the quality of reconstructed images for low-dose scans. MBIR is based on the penalized-likelihood (PL) approach, where the penalty term (also known as the regularizer) stabilizes the unstable likelihood term, thereby suppressing the noise. In this work we further improve MBIR by using a more expressive regularizer which can restore the underlying image more accurately. Here we used a spline regularizer derived from a linear combination of the two-dimensional splines with first- and second-order spatial derivatives and applied it to a non-quadratic convex penalty function. To derive a PL algorithm with the spline regularizer, we used a separable paraboloidal surrogates algorithm for convex optimization. The experimental results demonstrate that our regularization method improves reconstruction accuracy in terms of both regional percentage error and contrast recovery coefficient by restoring smooth edges as well as sharp edges more accurately.

CT Image Reconstruction of Wood Using Ultrasound Velocities II - Determination of the Initial Model Function of the SIRT Method -

  • Kim, Kwang-Mo;Lee, Jun-Jae
    • Journal of the Korean Wood Science and Technology
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    • v.33 no.5 s.133
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    • pp.29-37
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    • 2005
  • A previous study verified that the SIRT (simultaneous iterative reconstruction technique) method is more efficient than the back-projection method as a CT algorithm for wood. However, it was expected that the determination of the initial model function of the SIRT method would influence the quality of CT image. Therefore, in this study, we intended to develop a technique that could be used to determine an adequate initial model function. For this purpose, we proposed several techniques, and for each technique we examined the effects of the initial model function on the average errors and the CT image at each iteration. Through this study, it was shown that the average error was decreased and the image quality was improved using the proposed techniques. This tendency was most pronounced when the back-projection method was used to determine the initial model function. From the results of this study, we drew the following conclusions: 1) The initial model function of the SIRT method should be determined with careful attention, and 2) the back-projection method efficiently determines the initial model function of the SIRT method.

A Spline-Regularized Sinogram Smoothing Method for Filtered Backprojection Tomographic Reconstruction

  • Lee, S.J.;Kim, H.S.
    • Journal of Biomedical Engineering Research
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    • v.22 no.4
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    • pp.311-319
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    • 2001
  • Statistical reconstruction methods in the context of a Bayesian framework have played an important role in emission tomography since they allow to incorporate a priori information into the reconstruction algorithm. Given the ill-posed nature of tomographic inversion and the poor quality of projection data, the Bayesian approach uses regularizers to stabilize solutions by incorporating suitable prior models. In this work we show that, while the quantitative performance of the standard filtered backprojection (FBP) algorithm is not as good as that of Bayesian methods, the application of spline-regularized smoothing to the sinogram space can make the FBP algorithm improve its performance by inheriting the advantages of using the spline priors in Bayesian methods. We first show how to implement the spline-regularized smoothing filter by deriving mathematical relationship between the regularization and the lowpass filtering. We then compare quantitative performance of our new FBP algorithms using the quantitation of bias/variance and the total squared error (TSE) measured over noise trials. Our numerical results show that the second-order spline filter applied to FBP yields the best results in terms of TSE among the three different spline orders considered in our experiments.

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Bundle Adjustment and 3D Reconstruction Method for Underwater Sonar Image (수중 영상 소나의 번들 조정과 3차원 복원을 위한 운동 추정의 모호성에 관한 연구)

  • Shin, Young-Sik;Lee, Yeong-jun;Cho, Hyun-Taek;Kim, Ayoung
    • The Journal of Korea Robotics Society
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    • v.11 no.2
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    • pp.51-59
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    • 2016
  • In this paper we present (1) analysis of imaging sonar measurement for two-view relative pose estimation of an autonomous vehicle and (2) bundle adjustment and 3D reconstruction method using imaging sonar. Sonar has been a popular sensor for underwater application due to its robustness to water turbidity and visibility in water medium. While vision based motion estimation has been applied to many ground vehicles for motion estimation and 3D reconstruction, imaging sonar addresses challenges in relative sensor frame motion. We focus on the fact that the sonar measurement inherently poses ambiguity in its measurement. This paper illustrates the source of the ambiguity in sonar measurements and summarizes assumptions for sonar based robot navigation. For validation, we synthetically generated underwater seafloor with varying complexity to analyze the error in the motion estimation.

A Phase Current Reconstruction Technique Using a Single Current Sensor for Interleaved Three-phase Bidirectional Converters

  • Lee, Young-Jin;Cho, Younghoon;Choe, Gyu-Ha
    • Journal of Electrical Engineering and Technology
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    • v.11 no.4
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    • pp.905-914
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    • 2016
  • This paper proposes a new phase current reconstruction technique for interleaved three-phase bidirectional dc-dc converters using a single current sensor. In the proposed current reconstruction algorithm, a single current sensor is employed at the dc-link, and the dc-link current information is sampled at either the peak or valley point of the pulse-width modulation (PWM) carriers regularly. From the obtained current information, all phase currents are reconstructed in a single PWM cycle. After that, the digital current controller is applied to achieve current balancing in each phase. Compare to the previous multiple current sensor method, the proposed strategy reduces the number of the current sensors in the interleaved three-phase bidirectional converter as well as reducing potential current sensing error caused by non-ideal characteristics of the multiple current sensors. The effectiveness of the proposed method is verified from the experiments based on a 3kW three-phase bidirectional converter prototype for the automotive battery charging application.

Stagewise Weak Orthogonal Matching Pursuit Algorithm Based on Adaptive Weak Threshold and Arithmetic Mean

  • Zhao, Liquan;Ma, Ke
    • Journal of Information Processing Systems
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    • v.16 no.6
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    • pp.1343-1358
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    • 2020
  • In the stagewise arithmetic orthogonal matching pursuit algorithm, the weak threshold used in sparsity estimation is determined via maximum iterations. Different maximum iterations correspond to different thresholds and affect the performance of the algorithm. To solve this problem, we propose an improved variable weak threshold based on the stagewise arithmetic orthogonal matching pursuit algorithm. Our proposed algorithm uses the residual error value to control the weak threshold. When the residual value decreases, the threshold value continuously increases, so that the atoms contained in the atomic set are closer to the real sparsity value, making it possible to improve the reconstruction accuracy. In addition, we improved the generalized Jaccard coefficient in order to replace the inner product method that is used in the stagewise arithmetic orthogonal matching pursuit algorithm. Our proposed algorithm uses the covariance to replace the joint expectation for two variables based on the generalized Jaccard coefficient. The improved generalized Jaccard coefficient can be used to generate a more accurate calculation of the correlation between the measurement matrixes. In addition, the residual is more accurate, which can reduce the possibility of selecting the wrong atoms. We demonstrate using simulations that the proposed algorithm produces a better reconstruction result in the reconstruction of a one-dimensional signal and two-dimensional image signal.

Spatial Frequency Coverage and Image Reconstruction for Photonic Integrated Interferometric Imaging System

  • Zhang, Wang;Ma, Hongliu;Huang, Kang
    • Current Optics and Photonics
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    • v.5 no.6
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    • pp.606-616
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    • 2021
  • A photonic integrated interferometric imaging system possesses the characteristics of small-scale, low weight, low power consumption, and better image quality. It has potential application for replacing conventional large space telescopes. In this paper, the principle of photonic integrated interferometric imaging is investigated. A novel lenslet array arrangement and lenslet pairing approach are proposed, which are helpful in improving spatial frequency coverage. For the novel lenslet array arrangement, two short interference arms were evenly distributed between two adjacent long interference arms. Each lenslet in the array would be paired twice through the novel lenslet pairing approach. Moreover, the image reconstruction model for optical interferometric imaging based on compressed sensing was established. Image simulation results show that the peak signal to noise ratio (PSNR) of the reconstructed image based on compressive sensing is about 10 dB higher than that of the direct restored image. Meanwhile, the normalized mean square error (NMSE) of the direct restored image is approximately 0.38 higher than that of the reconstructed image. Structural similarity index measure (SSIM) of the reconstructed image based on compressed sensing is about 0.33 higher than that of the direct restored image. The increased spatial frequency coverage and image reconstruction approach jointly contribute to better image quality of the photonic integrated interferometric imaging system.

Indirect displacement monitoring of high-speed railway box girders consider bending and torsion coupling effects

  • Wang, Xin;Li, Zhonglong;Zhuo, Yi;Di, Hao;Wei, Jianfeng;Li, Yuchen;Li, Shunlong
    • Smart Structures and Systems
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    • v.28 no.6
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    • pp.827-838
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    • 2021
  • The dynamic displacement is considered to be an important indicator of structural safety, and becomes an indispensable part of Structural Health Monitoring (SHM) system for high-speed railway bridges. This paper proposes an indirect strain based dynamic displacement reconstruction methodology for high-speed railway box girders. For the typical box girders under eccentric train load, the plane section assumption and elementary beam theory is no longer applicable due to the bend-torsion coupling effects. The monitored strain was decoupled into bend and torsion induced strain, pre-trained multi-output support vector regression (M-SVR) model was employed for such decoupling process considering the sensor layout cost and reconstruction accuracy. The decoupled strained based displacement could be reconstructed respectively using box girder plate element analysis and mode superposition principle. For the transformation modal matrix has a significant impact on the reconstructed displacement accuracy, the modal order would be optimized using particle swarm algorithm (PSO), aiming to minimize the ill conditioned degree of transformation modal matrix and the displacement reconstruction error. Numerical simulation and dynamic load testing results show that the reconstructed displacement was in good agreement with the simulated or measured results, which verifies the validity and accuracy of the algorithm proposed in this paper.

Analyzing the Influence of Spatial Sampling Rate on Three-dimensional Temperature-field Reconstruction

  • Shenxiang Feng;Xiaojian Hao;Tong Wei;Xiaodong Huang;Pan Pei;Chenyang Xu
    • Current Optics and Photonics
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    • v.8 no.3
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    • pp.246-258
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    • 2024
  • In aerospace and energy engineering, the reconstruction of three-dimensional (3D) temperature distributions is crucial. Traditional methods like algebraic iterative reconstruction and filtered back-projection depend on voxel division for resolution. Our algorithm, blending deep learning with computer graphics rendering, converts 2D projections into light rays for uniform sampling, using a fully connected neural network to depict the 3D temperature field. Although effective in capturing internal details, it demands multiple cameras for varied angle projections, increasing cost and computational needs. We assess the impact of camera number on reconstruction accuracy and efficiency, conducting butane-flame simulations with different camera setups (6 to 18 cameras). The results show improved accuracy with more cameras, with 12 cameras achieving optimal computational efficiency (1.263) and low error rates. Verification experiments with 9, 12, and 15 cameras, using thermocouples, confirm that the 12-camera setup as the best, balancing efficiency and accuracy. This offers a feasible, cost-effective solution for real-world applications like engine testing and environmental monitoring, improving accuracy and resource management in temperature measurement.

Error Concealment Using a Digital Watermarking Technique for Interframe Video Coding

  • Munadi, Khairul;Kurosaki, Masayuki;Kiya, Hitoshi
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.599-602
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    • 2002
  • A new approach of error concealment using a digital watermarking technique for interframe video coding is presented in this paper. In the proposed method, the most important feature of the reference frame is extracted. Then, this feature is embedded into the prediction error of current frame prior to transmission. Error concealment is achieved by means of recovering the erroneous reference frame using the embedded data before the reconstruction of current frame is performed. Simulation results demonstrated the effectiveness of the proposed method.

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