• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.181-190
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• 2013

We propose an interpolation method considering barrel distortion of fisheye lens using nearest pixels on a corrected image. The correction of barrel distortion comprises coordinate transformation and interpolation. This paper focuses on interpolation. The proposed interpolation method uses nearest four coordinates on a corrected image rather than on a distorted image unlike existing techniques. Experimental results show that both subjective and objective image qualities are improved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.672-675
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• 2001

In this paper, we propose that the calculation method for accurate wind speed using interpolation methods, and the finding method for accurate wind direction using interpolation polynomial, so we make better performance for 3-Cup Anemometer by the proposed methods. We embody the 3-Cup Anemometer with photo sensor to measure wind direction and wind speed. In order to more accurate wind speed and wind direction, we present the methods to overcome the limitations of system memory and of the sensor measurement error by 8 bit gray code (as substitute 360 degrees for 256 degrees data).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.2
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• pp.81-90
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• 2017

This study aimed to construct an integrated database using the same spatio-temporal unit by employing various public-data types with different real-time information provision cycles and spatial units. Towards this end, three temporal interpolation methods (piecewise constant interpolation, linear interpolation, nonlinear interpolation) and a spatial matching method by district boundaries was proposed. The case study revealed that the linear interpolation is an excellent method, and the spatial matching method also showed good results. It is hoped that various prediction models and data analysis methods will be developed in the future using different types of data in the analysis database.

• Journal of Environmental Impact Assessment
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• v.15 no.6
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• pp.443-452
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• 2006

Today, satellite remote sensing (RS) and geographic information systems (GIS) plays an important role as an advanced science and technology. This study was developed a Line Density Algorithm which was clarify and describe the thermal front by using NOAA SST (sea surface temperature) and GIS spatial analysis for systemic and effective management of fish raising industry and sea environmental pollution by land reclamation program. Before this, a study about a interpolation method was carry out which was very important for estimate the hidden value between a special point. For this study Inverse Distance Weighted interpolation, Spline interpolation, Kriging interpolation methods were choose and SST data from 2001 to 2004 in spring (March, April, May) were analyzed. According to the study Kriging interpolation method was the very adaptive method from a practical point of view and excellent in description and precision then others. Finally, the result of this study will be use for develope the Line Density Index Algorism.

• Journal of Korea Multimedia Society
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• v.5 no.5
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• pp.494-504
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• 2002

Volume rendering is a method of displaying volumetric data as a sequence two-dimensional image. Because this algorithm has an advantage of visualizing structures within objects, it has recently been used to analyze medical images i.e, MRI, PET, and SPECT. In this paper. we suggested a method for creating images easily from sampled volumetric data and applied the interpolation method to medical images. Additionally, we implemented and applied two kinds of interpolation methods to improve the image quality, linear interpolation and cubic interpolation at the sampling stage. Subsequently, we compared the results of volume rendered data using a transfer function. We anticipate a significant contribution to diagnosis through image reconstruction using a volumetric data set, because volume rendering techniques of medical images are the result of 3-dimensional data.

• Wind and Structures
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• v.39 no.2
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• pp.125-140
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• 2024

The simulation of non-stationary wind velocity is particularly crucial for the wind resistant design of slender structures. Recently, some data-driven simulation methods have received much attention due to their straightforwardness. However, as the number of simulation points increases, it will face efficiency issues. Under such a background, in this paper, a time-varying coherence matrix decomposition method based on Diagonal Proper Orthogonal Decomposition (DPOD) interpolation is proposed for the data-driven simulation of non-stationary wind velocity based on S-transform (ST). Its core idea is to use coherence matrix decomposition instead of the decomposition of the measured time-frequency power spectrum matrix based on ST. The decomposition result of the time-varying coherence matrix is relatively smooth, so DPOD interpolation can be introduced to accelerate its decomposition, and the DPOD interpolation technology is extended to the simulation based on measured wind velocity. The numerical experiment has shown that the reconstruction results of coherence matrix interpolation are consistent with the target values, and the interpolation calculation efficiency is higher than that of the coherence matrix time-frequency interpolation method and the coherence matrix POD interpolation method. Compared to existing data-driven simulation methods, it addresses the efficiency issue in simulations where the number of Cholesky decompositions increases with the increase of simulation points, significantly enhancing the efficiency of simulating multivariate non-stationary wind velocities. Meanwhile, the simulation data preserved the time-frequency characteristics of the measured wind velocity well.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.681-683
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• 2017

In the digital information age, image processing is essential for various digital devices such as smart phones, cameras, and TVs. However, degradation occurs in analyzing, recognizing, and processing image data, and salt & pepper noise occurs. Therefore, in this paper, we applied linear interpolation method, newton interpolation method, lagrange interpolation method, and spline interpolation method to the image damaged by salt & pepper noise in order to find more effective interpolation method in salt & pepper noise environment, The methods were compared using the PSNR (peak signal to noise ratio).

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.12
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• pp.820-826
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• 2004

In this paper, studied error of various signal interpolation methods in vibration signal analysis with digital order tracking. Because, interpolation errors are related with sampling rate and amount of calculation. Appled Signal interpolation methods are Lagrange, Newton and Cubic-spline. This paper proposed more proper interpolation method. Also, we suggest guideline for adaptive application of signal interpolation methods with Calculated results.

• The Journal of Engineering Geology
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• v.33 no.3
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• pp.439-459
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• 2023

Numerical analysis has been adopted in nearly all modern scientific and engineering fields due to the rapid and ongoing evolution of computational technology, with the number of grid or mesh points in a given data field also increasing. Some values must be extracted from large data fields to evaluate and supplement numerical analysis results and observational data, thereby highlighting the need for a fast and effective interpolation approach. The quadrilateral irregular network (QIN) proposed in this study is a fast and reliable interpolation method that is capable of sufficiently satisfying these demands. A comparative sensitivity analysis is first performed using known test functions to assess the accuracy and computational requirements of QIN relative to conventional interpolation methods. These same interpolation methods are then employed to produce simple numerical model results for a real-world comparison. Unlike conventional interpolation methods, QIN can obtain reliable results with a guaranteed degree of accuracy since there is no need to determine the optimal parameter values. Furthermore, QIN is a computationally efficient method compared with conventional interpolation methods that require the entire data space to be evaluated during interpolation, even if only a subset of the data space requires interpolation.

• Journal of Information Display
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• v.5 no.3
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• pp.1-7
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• 2004

We developed a novel frame interpolation method to interpolate a frame between two successive original frames. Using this method, we are able to apply a double-rate driving method instead of an impulse driving method where a black frame is inserted between two successive original frames. The double-rate driving method enables amelioration of the motion blur of LCDs caused by the characteristics of human vision without reducing the luminosity of the whole screen. The image quality of the double-rate driving method was also found to be better than that of an impulse driving method using our motion picture simulator and an actual panel. Our initial model of our frame interpolation method consists of motion estimation with a maximum matching pixel count estimation function, an area segmentation technique, and motion compensation with variable segmentation threshold. Although salt and pepper noise remained in a portion of an object mainly due to inaccuracy of motion estimation, we verified the validity of our method and the possibility of improvement in hold-type motion blurring.