• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.55-65
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• 2020

With the development of display hardware, image interpolation techniques have been used in various fields such as image zooming and medical imaging. Traditional image interpolation methods, such as bi-linear interpolation, bi-cubic interpolation and edge direction-based interpolation, perform interpolation in the spatial domain. Recently, interpolation techniques in the discrete cosine transform or wavelet domain are also proposed. Using these various existing interpolation methods and machine learning, we propose decision tree classification-based image interpolation methods. In other words, this paper is about the method of adaptively applying various existing interpolation methods, not the interpolation method itself. To obtain the decision model, we used Weka's J48 library with the C4.5 decision tree algorithm. The proposed method first constructs attribute set and select classes that means interpolation methods for classification model. And after training, interpolation is performed using different interpolation methods according to attributes characteristics. Simulation results show that the proposed method yields reasonable performance.

• 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.

• Journal of Industrial Technology
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• v.12
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• pp.69-76
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• 1992

An attempt has been made to determination the NC milling machine's tool-path through the adaptive parabolic interpolation method & the adaptive linear-parabolic interpolation method in consideration of the economical machining time. The algorithms for the above-mentioned interpolation methods have been designed and the numerical experiments for these methods have been conducted with the existing adaptive linear interpolation methods for comparision.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.640-642
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• 1998

When resampling an image to a new set of coordinates, there is often a noticeable loss in image quality. The interpolation kernel determines the quality of interpolation. In this paper, We think two interpolation methods: cubic-spline method, neural net method, at first study given interpolation method using spline and then present new interpolation methon using SOFM and LAM(neural net method), finally compare the performance of several interpolation methods including replication, bilinear, spline and new methods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.8
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• pp.1418-1423
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• 2016

The purpose of this research is to investigate the effect of sampling frequency on the photoplethysmography (PPG) and to evaluate the performance of interpolation methods for under-sampled PPG. We generated down-sampled PPG using 10 kHz-sampled PPG then evaluated waveshape changes with correlation coefficient. Correlation coefficient was significantly decreased at 50 Hz or below sampling frequency. We interpolated the down-sampled PPG using four interpolation method-linear, nearest, cubic spline and piecewise cubic Hermitt interpolation polynomial - then evaluated interpolation performance. As a result, it was shown that PPG waveform that was sampled over 20 Hz could be reconstructed by interpolation. Among interpolation methods, cubic spline interpolation showed the highest performance. However, every interpolation method has no or less effect on 5 Hz sampled PPG.

• 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.

• 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 Climate Change Research
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• v.5 no.4
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• pp.323-329
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• 2014

Since the terrain of Korea is complex, micro- as well as meso-climate variability is extreme by locations in Korea. In particular, air temperature of agricultural fields is influenced by topographic features of the surroundings making accurate interpolation of regional meteorological data from point-measured data. This study was carried out to compare spatial interpolation methods to estimate air temperature in agricultural fields surrounded by rugged terrains in South Korea. Four spatial interpolation methods including Inverse Distance Weighting (IDW), Spline, Ordinary Kriging (with the temperature lapse rate) and Cokriging were tested to estimate monthly air temperature of unobserved stations. Monthly measured data sets (minimum and maximum air temperature) from 588 automatic weather system(AWS) locations in South Korea were used to generate the gridded air temperature surface. As the result, temperature lapse rate improved accuracy of all of interpolation methods, especially, spline showed the lowest RMSE of spatial interpolation methods in both maximum and minimum air temperature estimation.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.4
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• pp.217-223
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• 2010

In the case of image magnification by using interpolation methods, interpolated pixels are estimated from the known pixels in source image. The magnified image is composed of the known pixels in source image and the interpolated pixels which is estimated. If the interpolated pixels are estimated to have the locality which is exists in real images, the magnified image is much closer to the real image. In this paper, an improved interpolation scheme is proposed to estimate pixels from the known pixels in source image using the locality which is exists in real images. The magnified image by using the proposed interpolation scheme is much closer to the real image. The performance of the proposed interpolation scheme is evaluated by using PSNR(Peak Signal to Noise Ratio) in experiment. The PSNR of the magnified image by using the proposed scheme is improved than that of the magnified images by using existing interpolation methods. So, the proposed interpolation scheme is an efficient interpolation method for the quality improvement of magnified image.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.28 no.2
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• pp.387-413
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• 1998

Image resampling is of particular interest in digital radiology. When resampling an image to a new set of coordinate, there appears blocking artifacts and image changes. To enhance image quality, interpolation algorithms have been used. Resampling is used to increase the number of points in an image to improve its appearance for display. The process of interpolation is fitting a continuous function to the discrete points in the digital image. The purpose of this study was to determine the effects of the seven interpolation functions when image resampling in digital periapical images. The images were obtained by Digora, CDR and scanning of Ektaspeed plus periapical radiograms on the dry skull and human subject. The subjects were exposed to intraoral X-ray machine at 60kVp and 70 kVp with exposure time varying between 0.01 and 0.50 second. To determine which interpolation method would provide the better image, seven functions were compared; (1) nearest neighbor (2) linear (3) non-linear (4) facet model (5) cubic convolution (6) cubic spline (7) gray segment expansion. And resampled images were compared in terms of SNR(Signal to Noise Ratio) and MTF(Modulation Transfer Function) coefficient value. The obtained results were as follows ; 1. The highest SNR value(75.96dB) was obtained with cubic convolution method and the lowest SNR value(72.44dB) was obtained with facet model method among seven interpolation methods. 2. There were significant differences of SNR values among CDR, Digora and film scan(P<0.05). 3. There were significant differences of SNR values between 60kVp and 70kVp in seven interpolation methods. There were significant differences of SNR values between facet model method and those of the other methods at 60kVp(P<0.05), but there were not significant differences of SNR values among seven interpolation methods at 70kVp(P>0.05). 4. There were significant differences of MTF coefficient values between linear interpolation method and the other six interpolation methods (P< 0.05). 5. The speed of computation time was the fastest with nearest -neighbor method and the slowest with non-linear method. 6. The better image was obtained with cubic convolution, cubic spline and gray segment method in ROC analysis. 7. The better sharpness of edge was obtained with gray segment expansion method among seven interpolation methods.