• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.10
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• pp.2425-2430
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• 2013

This paper presents an shifted linear interpolation method with an image-dependent parameter. The previous shifted linear interpolation proposed the optimal shift parameter of 0.21, which is calculated by spectrum analysis of the shifted linear interpolation kernel. However, the parameter can be different if we takes an input image spectrum into account. Thus, we introduce an image-dependent parameter. An experiment shows the best shift parameter is 0.19 in average for real images. Also, simulation results indicate the proposed method is superior to the existing shifted linear interpolation as well as conventional methods such as linear interpolation and cubic convolution interpolation in terms of the subjective and objective image quality.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.35.1-35
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• 2002

$\textbullet$ Sliding mode control (SMC) with nonlinear interpolation in variable boundary layer (VBL) is proposed $\textbullet$ A sigmoid function is used for nonlinear interpolation in VBL. $\textbullet$ The Parameter of the sigmoid function is tuned by fuzzy controller $\textbullet$ The choice of parameter for the sigmoid function is guided by FC. $\textbullet$ The parameter is continuously updated as boundary layer thickness varies. $\textbullet$ The proposed method hasbetter tracking performance than the conventional linear interpolation $\textbullet$ To demonstrate its performance the proposed control algorithm is applied to a nonlinear system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.957-960
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• 1995

A new method is introduced for the parametrization in B-spline surface interpolation. THis method uses the basis function to assign the parameter values to the arbitrary set of geometric data. This method gives us several important advantages in geometric modeling.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1810-1815
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• 2003

Sliding mode control with nonlinear interpolation in the boundary layer is proposed. A modified sigmoid function is used for nonlinear interpolation in the boundary layer and its parameter is tuned by a fuzzy logic controller. The fuzzy logic controller that takes the distance between the system state and the sliding surface as its input guides the choice of parameter of the modified sigmoid function and the parameter is on-line tuned. Owing to the decreased thickness, the proposed method has better tracking performance than the conventional linear interpolation method. To demonstrate its performance, the proposed control algorithm is applied to a simple nonlinear system model.

• Korean Journal of Computational Design and Engineering
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• v.3 no.4
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• pp.243-250
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• 1998

In parametric surface interpolation, the choice of the parameter values to the set of scattered points makes a great deal of difference in the resulting surface. A new method is developed and tested for the parametrization in NURBS surface global interpolation. This method uses the parameter value at the maximal value of relevant rational basis function, to assign the parameter values to the arbitrary set of design data. This method gives us several important advantages in geometric modeling, the freedom of the selection of knot values, the feasible transformation of the data set to the matrix, the possibility of affinite transformation between the design data and generated surface, etc.

• Journal of Industrial Technology
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• v.28 no.A
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• pp.27-34
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• 2008

The purpose of this paper is an adaptive image interpolation using parametric cubic convolution. Proposed method derive parameter of adapting the frequency from adjacent values. The parameter optimize the interpolation kernel of cubic convolution. Simulation results show that the proposed method is superior to the conventional method in terms of the subjective and objective image quality.

• Journal of Korea Multimedia Society
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• v.9 no.8
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• pp.1000-1009
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• 2006

We propose an adaptive linear interpolation locating sub-pixels. We utilize a pixel-based parameter in the conventional linear interpolation. To optimally obtain the parameter, we propose a generic interpolation structure including a low pass filter and minimum mean square error. We also propose a simple version of the generic interpolation method, which obtain a closed-form solution. Simulation results show that the proposed method is superior to the state-of-the-art methods such as warped distance linear interpolation and shifted linear interpolation, as well as the conventional method such as the linear interpolation and the cubic convolution interpolation in terms of the subjective and objective image quality.

• The Journal of Korean Association of Computer Education
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• v.11 no.5
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• pp.57-66
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• 2008

An adaptive optimization of parametric cubic convolution for image interpolation is derived in this paper. The proposed technique is based on optimizing the standard cubic convolution interpolation formula at each interpolated pixel. Conventional parametric cubic convolution methods use a fixed parameter in an image, so properties of each pixel cannot be incorporated into the interpolation. The proposed method optimizes the interpolation kernel by obtaining parameters adaptively on each pixel. A new cost function is introduced to reflect frequency properties of the original data. The proposed technique produces noticeably sharper edges than traditional techniques and exhibits an average PSNR improvement of traditional techniques.

• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.523-529
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• 2004

Sliding mode control with nonlinear interpolation in the boundary layer is proposed. A modified sigmoid function is used for nonlinear interpolation in the boundary layer and its parameter is tuned by a fuzzy controller. The fuzzy controller that takes both the sliding variable and a measure of chattering as its inputs tunes the parameter of the modified sigmoid function. Owing to the decreased thickness of the boundary layer and the tuned parameter, the proposed method has superior tracking performance than the conventional linear interpolation method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.11
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• pp.1455-1461
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• 2018

This paper presents a kernel analysis of weighted linear interpolation based on even-odd decomposition (EOD). The EOD method has advantages in that it provides low-complexity and improved image quality than the CCI method. However, since the kernel of EOD has not studied before and its analysis has not been addressed yet, this paper proposes the kernel function and its analysis. The kernel function is divided into odd and even terms. And then, the kernel is accomplished by summing the two terms. The proposed kernel is adjustable by a parameter. The parameter influences efficiency in the EOD based WLI process. Also, the kernel shapes are proposed by adjusting the parameter. In addition, the discussion with respect to the parameter is given to understand the parameter. A preliminary experiment on the kernel shape is presented to understand the adjustable parameter and corresponding kernel.