• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.9 no.2
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• pp.29-43
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• 2005

We consider a surface reconstruction problem from geometrical points (i.e., points given without any order) distributed on a series of smooth parallel cross sections in ${\mathbb{R}}^3$. To solve the problem, we utilize the natural points ordering method in ${\mathbb{R}}^2$, described in [18], which is a method of reconstructing a curve from a set of sample points and is based on the concept of diffusion motions of a small object from one point to the other point. With only the information of the positions of these geometrical points, we construct an acceptable surface consisting of triangular facets using a heuristic algorithm to link a pair of parallel cross-sections constructed via the natural points ordering method. We show numerical simulations for the proposed algorithm with some sets of sample points.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1145-1148
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• 2002

This paper presents a new method which is calculated to use only three vanishing points in order to compute the dimensions of object and its pose from a single image of perspective projection taken by a camera and the problem of recovering 3D models from three vanishing points of box scene. Our approach is to compute only three vanishing points without this information such as the focal length, rotation matrix, and translation from images in the case of perspective projection. We assume that the object can be modeled as a linear function of a dimension vector ν. The input of reconstruction is a set of correspondences between features in the model and features in the image. To minimize each the dimensions of the parameterized models, this reconstruction of optimization can be solved by the standard nonlinear optimization techniques with a multi-start method which generates multiple starting points for the optimizer by sampling the parameter space uniformly.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.6
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• pp.431-438
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• 2005

Bubble behaviors in a circular tube have been analyzed numerically and experimentally by a three-dimensional tomography method, Initially, a multiplicative algebraic reconstruction technique (MART) which showed better results for previous studies of numerical simulations has been performed to confirm the accuracy of the three-dimensional reconstruction for the two-phase flow using a computer-synthesized phantom, Then, bubble behaviors have been investigated experimentally by the three-dimensional MART method using real projected data captured simultaneously by a laser and three CCD cameras for three angles of view, Also, the transient reconstructions have been attempted to analyze the real-time oxygen-bubble movements in water by the interval of 1/30 second.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.8-14
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• 2009

In this paper, a convex optimization technique, which is based on the generalized quantization constraint (GQC), is proposed in the compressive sensing reconstruction using quantized measures. The set size of the proposed GQC can be controlled, and through extensive numerical simulations based on the uniform scalar quantizers, the CS reconstruction errors are improved by 3.4-3.6dB compared to the traditional QC method for the CS problems of m/klogn > 2.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.2
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• pp.59-64
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• 2001

In this paper, we propose an alternate method for determining the uniqueness of the reconstruction of a complex sequence from its phase. Uniqueness constraints could be derived in terms of the zeros of a complex polynomial defined by the DFT of the sequence. However, rooting of complex polynomials of high order is a very difficult problem. Instead of finding zeros of a complex polynomial, the proposed uniqueness criteria show that non-singularity of a matrix can guarantee the uniqueness of the reconstruction of a complex sequence from its phase-only data. It has clear advantage over the rooting method in numerical stability and computational time.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.410-421
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• 2019

Distributed compressed sensing (DCS) states that we can recover the sparse signals from very few linear measurements. Various studies about DCS have been carried out recently. In many practical applications, there is no prior information except for standard sparsity on signals. The typical example is the sparse signals have block-sparse structures whose non-zero coefficients occurring in clusters, while the cluster pattern is usually unavailable as the prior information. To discuss this issue, a new algorithm, called backtracking-based adaptive orthogonal matching pursuit for block distributed compressed sensing (DCSBBAOMP), is proposed. In contrast to existing block methods which consider the single-channel signal reconstruction, the DCSBBAOMP resorts to the multi-channel signals reconstruction. Moreover, this algorithm is an iterative approach, which consists of forward selection and backward removal stages in each iteration. An advantage of this method is that perfect reconstruction performance can be achieved without prior information on the block-sparsity structure. Numerical experiments are provided to illustrate the desirable performance of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.10
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• pp.911-919
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• 2013

Evaluation of the effect of radial distortion for a holographic stereogram demands conducting an experiment which comprises rendering of a 3D obejc, acquisition of perspective images, rearrangement of the acquired images for hogel images and quality assessment of the observing image reconstructed from the holographic stereogram. We propose numerical implementation of this evaluation by a specially developed algorithm for modeling of all required steps. The modeling is done by using a numerical model of an optical engine for generation of radially distorted hogel images at various degrees of distortion. The distorted images are used to form the holographic stereogram and to make the numerically reconstructed images from the holographic stereogram which are observed by an observer at desired location. The reconstructed images are compared by using PSNR.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2480-2484
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• 2005

Electrical resistance tomograpy (ERT) maps resistivity values of the soil subsurface and characterizes buried objects. The characterization includes location, size, and resistivity of buried objects. In this paper, truncated least squares (TLS) is presented for the solution of the ERT image reconstruction. Results of numerical experiments in ERT solved by the TLS approach is presented and compared to that obtained by the Gauss-Newton method.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2721-2723
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• 2002

Electrical impedance tomograpy(EIT) determines the resistivity distribution inside an inhomogeneous target by means of voltage and current measurements conducted at the target boundary. In this paper, a simultaneous perturbation stochastic approximation(SPSA) approach is proposed for the solution of the EIT image reconstruction. Results of numerical experiments of EIT solved by the SPSA approach are presented and compared to that obtained by the modified Newton-Raphson(mNR) method.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.225-230
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• 1997

Discrete Wavelet Transforms (DWTs) are recent mathematics, and begin to be used in various fields. The wavelet transform can be used to compress the signal and image due to its inherent properties. We applied the wavelet transform compression and reconstruction to the neutron cross section data. Numerical tests illustrate that tile signal compression using wavelet is very effective to reduce the data saving spaces.