• Title/Summary/Keyword: Iterative reconstruction

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Design of a Mapping Framework on Image Correction and Point Cloud Data for Spatial Reconstruction of Digital Twin with an Autonomous Surface Vehicle (무인수상선의 디지털 트윈 공간 재구성을 위한 이미지 보정 및 점군데이터 간의 매핑 프레임워크 설계)

  • Suhyeon Heo;Minju Kang;Jinwoo Choi;Jeonghong Park
    • Journal of the Society of Naval Architects of Korea
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    • v.61 no.3
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    • pp.143-151
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    • 2024
  • In this study, we present a mapping framework for 3D spatial reconstruction of digital twin model using navigation and perception sensors mounted on an Autonomous Surface Vehicle (ASV). For improving the level of realism of digital twin models, 3D spatial information should be reconstructed as a digitalized spatial model and integrated with the components and system models of the ASV. In particular, for the 3D spatial reconstruction, color and 3D point cloud data which acquired from a camera and a LiDAR sensors corresponding to the navigation information at the specific time are required to map without minimizing the noise. To ensure clear and accurate reconstruction of the acquired data in the proposed mapping framework, a image preprocessing was designed to enhance the brightness of low-light images, and a preprocessing for 3D point cloud data was included to filter out unnecessary data. Subsequently, a point matching process between consecutive 3D point cloud data was conducted using the Generalized Iterative Closest Point (G-ICP) approach, and the color information was mapped with the matched 3D point cloud data. The feasibility of the proposed mapping framework was validated through a field data set acquired from field experiments in a inland water environment, and its results were described.

CT Image Reconstruction of Wood Using Ultrasound Velocities I - Effects of Reconstruction Algorithms and Wood Characteristics -

  • 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.21-28
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    • 2005
  • For the proper conservation of wooden cultural properties, non-destructive evaluation (NDE) method, which can be used to quantitatively evaluate the internal state of wood members, are needed. In this study, an ultrasonic CT system composed of portable devices was attempted, and the capacity of this system was verified by reconstructing the CT images for two phantoms and two artificially defected specimens. Results from this study showed that the sizes of detected defects were enlarged and the shapes were distorted on the CT images. Also, the positions were shifted somewhat toward the surface of specimen, which is regarded due to the anisotropic property of wood. Compared to the filtered back-projection method, SIRT (simultaneous iterative reconstruction technique) method was determined to be more efficient as the algorithm of image reconstruction for wood. A new ultrasonic CT system is thought to be used as a NDE method for wood. However wood characteristics and wave diffraction within wood made it difficult to accurately evaluate the size, shape and position of defects. To improve the quality of CT image of wood, more research including the relationship between wood and ultrasound is needed, and wood properties should be taken into consideration on the image reconstruction algorithm.

Marker-less Calibration of Multiple Kinect Devices for 3D Environment Reconstruction (3차원 환경 복원을 위한 다중 키넥트의 마커리스 캘리브레이션)

  • Lee, Suwon
    • Journal of Korea Multimedia Society
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    • v.22 no.10
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    • pp.1142-1148
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    • 2019
  • Reconstruction of the three-dimensional (3D) environment is a key aspect of augmented reality and augmented virtuality, which utilize and incorporate a user's surroundings. Such reconstruction can be easily realized by employing a Kinect device. However, multiple Kinect devices are required for enhancing the reconstruction density and for spatial expansion. While employing multiple Kinect devices, they must be calibrated with respect to each other in advance, and a marker is often used for this purpose. However, a marker needs to be placed at each calibration, and the result of marker detection significantly affects the calibration accuracy. Therefore, a user-friendly, efficient, accurate, and marker-less method for calibrating multiple Kinect devices is proposed in this study. The proposed method includes a joint tracking algorithm for approximate calibration, and the obtained result is further refined by applying the iterative closest point algorithm. Experimental results indicate that the proposed method is a convenient alternative to conventional marker-based methods for calibrating multiple Kinect devices. Hence, the proposed method can be incorporated in various applications of augmented reality and augmented virtuality that require 3D environment reconstruction by employing multiple Kinect devices.

Super-Resolution Image Reconstruction Using Multi-View Cameras (다시점 카메라를 이용한 초고해상도 영상 복원)

  • Ahn, Jae-Kyun;Lee, Jun-Tae;Kim, Chang-Su
    • Journal of Broadcast Engineering
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    • v.18 no.3
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    • pp.463-473
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    • 2013
  • In this paper, we propose a super-resolution (SR) image reconstruction algorithm using multi-view images. We acquire 25 images from multi-view cameras, which consist of a $5{\times}5$ array of cameras, and then reconstruct an SR image of the center image using a low resolution (LR) input image and the other 24 LR reference images. First, we estimate disparity maps from the input image to the 24 reference images, respectively. Then, we interpolate a SR image by employing the LR image and matching points in the reference images. Finally, we refine the SR image using an iterative regularization scheme. Experimental results demonstrate that the proposed algorithm provides higher quality SR images than conventional algorithms.

Adaptive MAP High-Resolution Image Reconstruction Algorithm Using Local Statistics (국부 통계 특성을 이용한 적응 MAP 방식의 고해상도 영상 복원 방식)

  • Kim, Kyung-Ho;Song, Won-Seon;Hong, Min-Cheol
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.12C
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    • pp.1194-1200
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    • 2006
  • In this paper, we propose an adaptive MAP (Maximum A Posteriori) high-resolution image reconstruction algorithm using local statistics. In order to preserve the edge information of an original high-resolution image, a visibility function defined by local statistics of the low-resolution image is incorporated into MAP estimation process, so that the local smoothness is adaptively controlled. The weighted non-quadratic convex functional is defined to obtain the optimal solution that is as close as possible to the original high-resolution image. An iterative algorithm is utilized for obtaining the solution, and the smoothing parameter is updated at each iteration step from the partially reconstructed high-resolution image is required. Experimental results demonstrate the capability of the proposed algorithm.

Pin Power Reconstruction of HANARO Fuel Assembly via Gamma Scanning and Tomography Method

  • Seo, Chul-Gyo;Park, Chang-Je;Cho, Nam-Zin;Kim, Hark-Rho
    • Nuclear Engineering and Technology
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    • v.33 no.1
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    • pp.25-33
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    • 2001
  • To determine the pin power distribution without disassembling, HANARO fuel assemblies are gamma-scanned and then the distribution is reconstructed tv using the tomography method. The iterative least squares method (ILSM and the wavelet singular value decomposition method (WSVD) are chosen to solve the problem. An optimal convergence criterion is used to stop the iteration algorithm to overcome the potential divergence in ILSM. WSVD gives better results than ILSM , and the average values from the two methods give the best results. The RMSE (root mean square errors) to the reference data are 5.1, 6.6, 5.0, 6.5, and 6.4% and the maximum relative errors are 10.2, 13.7, 12.2, 13.6, and 14.3%, respectively. It is found that the effect of random positions of the pins is important. Although the effect can be accommodated by the iterative calculations simulating the random positions, the use of experimental equipment with a slit covering the whole range of the assembly horizontally is recommended to obtain more accurate results. We made a new apparatus using the results of this study and are conducting an experiment in order to obtain more accurate results.

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A Proposal of New Method for EICT Image Reconstruction A Hybrid Approach Using Genetic Algorithm and Newton-Raphson Method - (전기적 임피던스에 의한 컴퓨터 단층촬영 영상의 재구성의 위한 새로운 방법의 제안 - 유전알고리즘과 뉴으튼-랩슨법을 이용한 복합방법 -)

  • 조경호;고성택;고한석
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.4
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    • pp.91-99
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    • 1996
  • A hybrid approach employing both the genetic algorithm and the newton-raphson method is proposed for the electrical impedance computed tomography (EICT) image reconstruction. Computational experiments based on the new concept have shown promising results for several noise-free models. In particular, the resistance distribution of the tested models having resistivity ratio up to 100:1 has been reconstructed sucessfully. Using the proposed mehtod, it is also possible to get the reconstruction by the conventional iterative approaches be difficult to vonverge to a robust solution. If the compution power is enhanced further, the proposed method is expected to stimulate the practical applications of the EICT technology in the near future.

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Block Sparse Signals Recovery via Block Backtracking-Based Matching Pursuit Method

  • Qi, Rui;Zhang, Yujie;Li, Hongwei
    • Journal of Information Processing Systems
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    • v.13 no.2
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    • pp.360-369
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    • 2017
  • In this paper, a new iterative algorithm for reconstructing block sparse signals, called block backtracking-based adaptive orthogonal matching pursuit (BBAOMP) method, is proposed. Compared with existing methods, the BBAOMP method can bring some flexibility between computational complexity and reconstruction property by using the backtracking step. Another outstanding advantage of BBAOMP algorithm is that it can be done without another information of signal sparsity. Several experiments illustrate that the BBAOMP algorithm occupies certain superiority in terms of probability of exact reconstruction and running time.

A Volume Reconstruction Algorithm and a Coordinate Calibration of an X-ray Three Dimensional Imaging System

  • Roh, Young-Jun;Cho, Hyung-Suck;Jeon, Hyoung-Jo;Kim, Hyeong-Cheol
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.63.3-63
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    • 2001
  • Inspection and shape measurement of three-dimensional objects are widely needed in industries for quality monitoring and control. In this paper, we propose a three dimensional volume reconstruction method, which is an iterative method and as uniform and simulated algebraic reconstruction technique (USART). In this method, two or more x-ray images projected from different views are needed, and also the geometry of the imaging system need to be a priori identified well. That is to say, the relative locations between the x-ray source, imaging plane and the object should be determined exactly by calibration. To achieve this, we propose a series of coordinate calibration methods of the x-ray imaging system using grid pattern images. Some experimental results of these calibrations is presented and discussed in detail ...

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Image Reconstruction from Incomplete Data using a New Sampling Scheme (새로운 샘플링 방법을 이용한 불완전한 데이타로 부터 영상 재구성)

  • Jung, Byung-Moon;Park, Kil-Houm;Ha, Yeong-Ho
    • Proceedings of the KIEE Conference
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    • 1988.07a
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    • pp.232-235
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    • 1988
  • Recently, an iterative reconstruction-reprojection (IRR) algorithm has been suggested for application to incomplete data computed tomography (CT). In the IRR, the interpolation operation is performed in the image space during reconstruction-reprojection. The errors associated with the interpolation degrade the reconstructed image and may cause divergence unless a large number of rays is used. In this paper, we propose an improved IRR algorithm which eliminates the need for interpolation. The proposed algorithm adopts a new sampling scheme in which samples (projection data) is taken in phase with the samples of the Cartesian grid.

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