• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.434-442
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• 2008

The parallel beam SPECT acquires projection data by using parallel hole collimators in conjunction with photon detectors. Those projection data of the parallel beam SPECT are, however, contaminated by the distance dependent blurring because of the inaccuracy of the point response function of the collimator that is used to define the range of directions where photons can be detected. Thus an efficient aperture correction is required. In this paper we propose a distance dependent backprojection method to overcome the time limitation of iterative aperture correction methods and the performance limitation of Fourier-Distance Relation based method. The proposed method achieves aperture correction and fast image reconstruction by replacing the distance independent backprojection of the direct image reconstruction with the distance dependent one. We conducted several simulations to compare the performance of the proposed method with that of the conventional Fourier-Distance Relation based method. The simulation result shows that the proposed method outperforms the Fourier-Distance Relation based method in spatial resolution and robustness against noise.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.156-162
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• 2007

The parallel beam SPECT system acquires projection data by using collimators in conjunction with photon detectors. The projection data of the parallel beam SPECT system is, however, blurred by the point response function of the collimator that is used to define the range of directions where photons can be detected. By increasing the number of parallel holes per unit area in collimator, one can reduce such blurring effect. This approach also, however, has the blurring problem if the distance between the object and the collimator becomes large. In this paper we consider correction methods for artifacts caused by non-circular orbit of parallel beam SPECT with many parallel holes per detector cell. To do so, we model the relationship between the object and its projection data as a linear system, and propose an iterative reconstruction method including artifacts correction. We compute the projector and the backprojector, which are required in iterative method, as a sum of convolutions with distance-dependent point response functions instead of matrix form, where those functions are analytically computed from a single function. By doing so, we dramatically reduce the computation time and memory required for the generation of the projector and the backprojector. We conducted several simulation studies to compare the performance of the proposed method with that of conventional Fourier method. The result shows that the proposed method outperforms Fourier methods objectively and subjectively.

• Proceedings of the IEEK Conference
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• 2000.11a
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• pp.505-508
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• 2000

The success of target reconstruction in SAR(Synthetic Aperture Radar) imaging system is greatly dependent on the coherent detection. Primary causes of incoherent detection are uncompensated target or sensor motion, random turbulence in propagation media, wrong path in radar platform, and etc. And these appear as multiplicative phase error to the echoed signal, which consequently, causes fatal degradations such as fading or dislocation of target image. In this paper, we present iterative phase error estimation scheme which uses echoed data in all temporal frequencies. We started with analyzing wave equation for one point target and extend to overall echoed data from the target scene - The two wave equations governing the SAR signal at two temporal frequencies of the radar signal are combined to derive a method to reconstruct the complex phase error function. Eventually, this operation attains phase error correction algorithm from the total received SAR signal. We verify the success of the proposed algorithm by applying it to the simulated spotlight-mode SAR data.

• Journal of the Korean Mathematical Society
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• v.58 no.3
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• pp.791-797
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• 2021

In this corrigendum, we offer a correction to [J. Korean Math. Soc. 54 (2017), No. 2, 461-477]. We construct a counterexample for the strengthened Cauchy-Schwarz inequality used in the original paper. In addition, we provide a new proof for Lemma 5 of the original paper, an estimate for the extremal eigenvalues of the standard unpreconditioned FETI-DP dual operator.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.140-148
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• 2013

This paper presents a iterative Bose-Chaudhuri-hocquenghem (i-BCH) code and its high-speed decoder architecture for 100 Gb/s optical communications. The proposed architecture features a very high data processing rate as well as excellent error correction capability. The proposed 6-iteration i-BCH code structure with interleaving method allows the decoder to achieve 9.34 dB net coding gain performance at $10^{-15}$ decoder output bit error rate to compensate for serious transmission quality degradation. The proposed high-speed i-BCH decoder architecture is synthesized using a 90-nm CMOS technology. It can operate at a clock frequency of 430 MHz and achieve a data processing rate of 100 Gb/s. Thus, it has potential applications in next generation forward error correction (FEC) schemes for 100 Gb/s optical communications.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.9
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• pp.57-66
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• 1994

In this paper, we present an iterative learning method of compensating for position sensor error. The previously known compensation algorithms need a special perfect position sensor or a priori information about error sources, while ours does not. to our best knowledge, any iterative learning approach has not been taken for sensor error compensation. Furthermore, our iterativelearning algorithm does not have the drawbacks of the existing interativelearning control theories. To be more specivic, our algorithm learns an uncertain function itself rather than its special time-trajectory and does not reuquest the derivatives of measurement signals. Moreover, it does not require the learning system to start with the same initial condition for all iterations. To illuminate the generality and practical use of our algorithm, we give the rigorous proof for its convergence and some experimental results.

• Korean Journal of Computational Design and Engineering
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• v.9 no.4
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• pp.397-405
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• 2004

Texture mapping is the process of covering 3D models with texture images in order to increase the visual realism of the models. For proper mapping the coordinates of texture images need to coincide with those of the 3D models. When projective images from the camera are used as texture images, the texture image coordinates are defined by a camera calibration method. The texture image coordinates are determined by the relation between the coordinate systems of the camera image and the 3D object. With the projective camera images, the distortion effect caused by the camera lenses should be compensated in order to get accurate texture coordinates. The distortion effect problem has been dealt with iterative methods, where the camera calibration coefficients are computed first without considering the distortion effect and then modified properly. The methods not only cause to change the position of the camera perspective line in the image plane, but also require more control points. In this paper, a new iterative method is suggested for reducing the error by fixing the principal points in the image plane. The method considers the image distortion effect independently and fixes the values of correction coefficients, with which the distortion coefficients can be computed with fewer control points. It is shown that the camera distortion effects are compensated with fewer numbers of control points than the previous methods and the projective texture mapping results in more realistic image.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.270-273
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• 2007

In this paper, a SAR-despeck1ing approach of adaptive iteration based a Bayesian model using the lognormal distribution for image intensity and a Gibbs random field (GRF) for image texture is proposed for noise removal of the images that are corrupted by multiplicative speckle noise. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. The MRF is incorporated into digital image analysis by viewing pixel types as states of molecules in a lattice-like physical system. The iterative approach based on MRF is very effective for the inner areas of regions in the observed scene, but may result in yielding false reconstruction around the boundaries due to using wrong information of adjacent regions with different characteristics. The proposed method suggests an adaptive approach using variable parameters depending on the location of reconstructed area, that is, how near to the boundary. The proximity of boundary is estimated by the statistics based on edge value, standard deviation, entropy, and the 4th moment of intensity distribution.

• Journal of Industrial Technology
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• v.15
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• pp.153-168
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• 1995

The purpose of this study is to develop a method for predicting the aerodynamic performance of the subsonic airfoils in the 2-dimensional, steady and viscous flow. For this study, the airfoil geometry is specified by adopting the longest chord line system and by considering local surface curvature. In case of the inviscid-incompressible flow, the analysis is accomplished by the linearly varying strength vortex panel method and the Karman-Tsien correction law is applied for the inviscid-compressible flow analysis. The Goradia's integral method and the Truckenbrodt integral method are adopted for the boundary layer analysis of the laminar flow and the turbulent flow respectively. Viscous and inviscid solutions are converged by the Lockheed iterative calculating method using the equivalent airfoil geometry. And the analysis of the seperated flow is performed using the Dvorak and Maskew's method as the basic method. The wake effect is also considered and its geometry expressed by the formula of Summey & Smith when no seperation occurs. A computational efficiency is verified by the comparison of the computational results with experimental data and by the shorter execution time.

• Journal of Auto-vehicle Safety Association
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• v.12 no.2
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• pp.33-39
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• 2020

This paper presents an Around View Monitoring (AVM) stop-line detection based longitudinal position correction algorithm for automated driving on urban roads. Poor positioning accuracy of low-cost GPS has many problems for precise path tracking. Therefore, this study aims to improve the longitudinal positioning accuracy of low-cost GPS. The algorithm has three main processes. The first process is a stop-line detection. In this process, the stop-line is detected using Hough Transform from the AVM camera. The second process is a map matching. In the map matching process, to find the corrected vehicle position, the detected line is matched to the stop-line of the HD map using the Iterative Closest Point (ICP) method. Third, longitudinal position of low-cost GPS is updated using a corrected vehicle position with Kalman Filter. The proposed algorithm is implemented in the Robot Operating System (ROS) environment and verified on the actual urban road driving data. Compared to low-cost GPS only, Test results show the longitudinal localization performance was improved.