• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.67-73
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• 2008

In the Markov network which models disparity map with the Markov Random Field(MRF), the belief propagation algorithm is operated by message passing between nodes corresponding to each pixels. Belief propagation algorithm required much iteration for accurate result. In this paper, we propose the stereo matching algorithm using belief propagation in multi-resolution domain. Multi-resolution method based on wavelet or lifting can reduce the search area, therefore this algorithm can generate disparity map with fast speed.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.7 no.4
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• pp.328-335
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• 1996

The numerical dispersive characteristics and the numerical stability confition of the Multi-Resolution Time-Domain(MRTD) method are calculated. A dispersion analysis of the MRTD schemes including a comparison to Yee's Finite-Difference Time-Domain(FDTD) method is given. The superiority of the MRTD method to the spatial discretization is shown. The required computational memory can be reduced by using the MRTD method. We expect that the MRTD method will be very useful method for numerical modelling of electromagnetics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.10
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• pp.2724-2730
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• 1996

In this paper, the dispersive characteristics of the Finite-Difference Frqequency-Domain method based on the Multi-Resolution Technique(MR-FDFD) are numerically analyzed. A dispersion analysis of the MR-FDFD ority of the MR-FDFD method to the spatial discretization is shown. We expect that the multi-resoluation technique will improve the disavantage of the finite difference techqnique which needs the large comutational memory for accurate electromagnetic analysis.

• Journal of computational fluids engineering
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• v.20 no.4
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• pp.44-50
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• 2015

The computational efficiency of flow simulations with Multi-resolution analysis (MRA) was enhanced via the boundary treatment of the computational domain. In MRA, an adaptive dataset to a solution is constructed through data decomposition with interpolating polynomial and thresholding. During the decomposition process, the basis points of interpolation should exceed the boundary of the computational domain. In order to resolve this problem, the weight coefficients of interpolating polynomial were adjusted near the boundaries. By this boundary treatment, the computational efficiency of MRA was enhanced while the numerical accuracy of a solution was unchanged. This modified MRA was applied to two-dimensional steady Euler equations and the enhancement of computational efficiency and the maintenance of numerical accuracy were assessed.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.447-448
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• 2006

In this paper, we propose tracking algorithm using multi resolution in wavelet transform domain. This algorithm consists of two steps. The first step is feature extraction that is select feature-points using 1-level wavelet transform in ROI (Region of Interest). The other step is feature tracking. Based on multi resolution of wavelet transform, we estimate a displacement between current frame and next frame on the basis of selected feature-points. Experimental results show that the proposed algorithm confirmed a better performance than a centroid tracking and correlation tracking.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.5
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• pp.271-274
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• 2014

Bayesian based Multi-Frame Super-Resolution (MF-SR) has been used as a popular and effective SR model. On the other hand, the texture region is not reconstructed sufficiently because it works on the spatial domain. In this study, the MF-SR method was extended to operate on the frequency domain to improve HF information as much as possible. For this, a spatially weighted bilateral total variation model was proposed as a regularization term for a Bayesian estimation. The experimental results showed that the proposed method can recover the texture region more realistically with reduced noise, compared to conventional methods.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2006-2009
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• 2005

This paper presents a method for registering images using phase correlation technique in fourier domain, hough transform and multi-resolution wavelet. To register images, source and input images are transformed to wavelet domain. An angular transition can be obtained by applying hough transform technique followed by phase correlation. Then we apply phase correlation technique to find x-axis and y-axis transition. We apply wavelet transform to reduce processing time and also use its coefficients as edge information instead of canny detector. With multi-resolution property of wavelet transform, registration time can be greatly reduced. After we get all transition parameters, we transform the input images according to these parameters. Then, we compose and blend all images into a new large image with details of all source images. From our experiment, we can find the accurate transition both x-y translation and angular transition with less error.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.991-1000
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• 2020

We propose a content-based image retrieval system that uses a combination of completed local binary pattern (CLBP) and color autocorrelogram. CLBP features are extracted on a multi-resolution multi-direction filtered domain of value component. Color autocorrelogram features are extracted in two dimensions of hue and saturation components. Experiment results revealed that the proposed method yields a lot of improvement when compared with the methods that use partial features employed in the proposed method. It is also superior to the conventional CLBP, the color autocorrelogram using R, G, and B components, and the multichannel decoded local binary pattern which is one of the latest methods.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.50-59
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• 1996

In this paper, a new hierarchical motion estiamtion scheme using the wavelet transformed multi-resolution image layers is proposed. Compared with the full search motion estimation method, the existing hierarchical methods remarkably reduce the amount of the computation but their efficiencies are depreciated by the local minima problem. In order to solve the local minima problem, the multi-resolution image layers are composed using the wavelet transform and the number of layers participated in the motion estimation for a block is determined by considering of its low band energy and higher band energy on the first wavelet transformed layer. The ratio between higher band energy and low band energy of each block is evaluated and in the case of the blocks which include relatively large higher band energy, the motion estimation is carried out in the high resolution layer. Otherwise, all layers are used. The final motion vectors are obtained in the first wavelet transformed layer. So less bits for motion vectors are transmitted, and the decomposition of received image using inverse wavelet transform decreases the blocking effect.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.7
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• pp.1131-1138
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• 2001

This paper presents the new Compact 2D Haar-wavelet-based MultiResolution Time-Domain method (MRTD) as an accelerating algorithm for the conventional Compact BD Finite-Difference Time-Domain method (FDTD). To validate this algorithm, we analyzed the dispersion characteristics of the hollow rectangular waveguide and dielectric slab-loaded rectangular waveguide. The results of the proposed method are very weal agreed with those of both the conventional analytic method and the Compact 2D FDTD method. The CPU time for analysis of this method is reduced to about a half of the conventional Compact 2D FDTD method. The proposed method is valuable as a fast algorithm in the research of dispersion characteristics of waveguide structures.