• Journal of applied mathematics & informatics
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• v.6 no.3
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• pp.771-771
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• 1999

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.241-248
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• 2007

In predictive image coding, a LS (Least Squares)-based adaptive predictor is an efficient method to improve image edge predictions. This paper proposes a hybrid interpolation with weighted edge detector. A hybrid approach of switching between bilinear interpolation and EDI (Edge-Directed Interpolation) is proposed in order to reduce the overall computational complexity The objective and subjective quality is also similar to the bilinear interpolation and EDI. Experimental results demonstrate that this hybrid interpolation method that utilizes a weighted edge detector can achieve reduction in complexity with minimal degradation in the interpolation results.

• Journal of the Korean association of regional geographers
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• v.10 no.2
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• pp.389-406
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• 2004

with the increasing popularity of regional studies, the importance of regional data has been recognized dramatically in recent years. However, due to potential problems from the intrinsic characteristics of aggregate regional data for the research, and incompatible regional units between source and target regional data units, the method for reorganizing the regional data units for a given research analysis should be required. In this regard, the purpose of this research is to review the significant interpolation methods for reorganizing the data units and, based on it, to propose the population weighted interpolation method. For the first purpose, areal weighted interpolation method, pycnophylactic method, dasymetric method, area-to-point method were reviewed. The proposed population-weighted interpolation method was applied to the case study of population census regional data in Erie County, NY, compared with areal weighted interpolation method, pycnophylactic method in terms of several statistical characteristics.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.3
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• pp.279-282
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• 2014

In this paper, we report a new sharp inequality of interpolation type in $\mathbb{R}^n$. This inequality is for controlling weighted average of a function via $L^n$ norm of the gradient of a function together with its' certain exponential norm.

• Journal of Broadcast Engineering
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• v.16 no.5
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• pp.873-882
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• 2011

In this paper, we propose an efficient deinterlacing algorithm which interpolates the missing scan lines by weighted summing of the intra and the inter interpolation pixels according to the spatio-temporal variation. In the spatial interpolation, we adopt a new edge based spatial interpolation method which includes edge directional refinement. The conventional edge dependent interpolation algorithms are very sensitive to noise due to the failure of estimating edge direction. In order to exactly detect edge direction, our method first finds the edge directions around the pixel to be interpolated and then refines edge direction of the pixel using weighted maximun frequent filter. Futhermore, we improve the accuracy of motion detection by reducing the possibility of motion detection error using 3 tab median filter. In the final interpolation step, we adopt weighted sum of intra and inter interpolation pixels according to spatio-temporal variation ratio, thereby improving the quality in slow moving area. Simulation results show the efficacy of the proposed method with significant improvement over the previous methods in terms of the objective PSNR quality as well as the subjective image quality.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.119-124
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• 2011

Interpolation filters are widely used in many communication and multimedia applications. Polynomial interpolation computes the coefficients of the polynomial according to the input information to obtain the interpolated value. Recently, FIR interpolation method using supplementary filters was proposed to improve the performances of polynomial interpolation methods. In this paper, by combining a weighting factor approach with the supplementary filter method, we propose a weighted interpolation method which can be efficiently used to compute the maximum or minimum values of a given curve using only a restricted number of sample values. With application to the interpolation of normal distribution curves used in XRF systems, it is shown that the proposed approach exhibits improved performances compared with conventional interpolation methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9C
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• pp.704-711
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• 2008

This paper proposes a new de-interlacing method which results in efficient visual improvement. In the proposed algorithm, the distance weight was considered and the previously developed the EDI (Edge Dependent Interpolation) algorithm and the NAL (New Adaptive Linear interpolation) algorithm were used as a basis. The do-interlacing method was divided into two main parts. First, the edge direction was found by using information of closer pixels. Then, missing pixels were interpolated along with the decided edge direction. In this paper, after predicting the edge through the EDI algorithm, missing pixels were interpolated by using the weighted distance based on the NAL algorithm. Experimental results indicate that the proposed algorithm be superior to the conventional algorithms in terms of the objective and subjective criteria.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.4
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• pp.453-459
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• 1988

A new interpolation function, named modified raised-cosine interpolation, is proposed. This function is derived from the linear combination of weighted triangular and raised-cosine functions to reduce the effect of side lobes which incur the interpolation error. Interpolation error reduces significantly for higher-order convolutional interpolation functions of linear operators, but at the expense of resolution error due to the attenuation of main lobe. However, the proposed interpolation function enables us to reduce the side lobes as well as to preserve the main lobe. To prove practicality, this function is applied in image reconstruction and enlargement.

• Geophysics and Geophysical Exploration
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• v.20 no.2
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• pp.78-87
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• 2017

For efficient data processing, trace interpolation and regularization techniques should be antecedently applied to the seismic data which were irregularly sampled with missing traces. Among many interpolation techniques, MWNI (Minimum Weighted Norm Interpolation) technique is one of the most versatile techniques and widely used to regularize seismic data because of easy extension to the high-order module and low computational cost. However, since it is difficult to interpolate spatially aliased data using this technique, model-constrained MWNI was suggested to compensate for this problem. In this paper, conventional MWNI and model-constrained MWNI modules have been developed in order to analyze their performance using synthetic data and validate the applicability to the field data. The result by using model-constrained MWNI was better in spatially aliased data. In order to verify the applicability to the field data, interpolation and regularization were performed for two field data sets, respectively. Firstly, the seismic data acquired in Ulleung Basin gas hydrate field was interpolated. Even though the data has very chaotic feature and complex structure due to the chimney, the developed module showed fairly good interpolation result. Secondly, very irregularly sampled and widely missing seismic data was regularized and the connectivity of events was quite improved. According to these experiments, we can confirm that the developed module can successfully interpolate and regularize the irregularly sampled field data.

• 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.