• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.85-99
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• 2020

Reservoir is an important infrastructure of our society because it can store immense amount of water for various usages - manufacturing, agriculture, drinking, power generation, tourism etc. For maintenance of reservoir, various efforts in administrative and technological aspects are periodically conducted and monitoring the conditions of reservoir bed is the first priority for maintenance of reservoir. To check the conditions of reservoir bed, we measured depth of reservoir by using echo sounder, which is relatively reliable, prior to discharging of stored water and surveyed topography of reservoir by using UAV after discharging of water. Then, we conducted interpolation of measured depth of water by means of inverse distance weighting interpolation, Kriging interpolation, minimum curvature interpolation and radial basis function interpolation and calculated the volume of reservoir for each interpolation method. We compared the calculated volume of reservoir with the volume of water calculated by UAV after discharging of water and found the following results: First, as results of the above processes, we found that the Kriging interpolation was 97% correct in measurement of the volume of reservoir. Second, as results of comparison of differences between topographical areas and interpolated areas after selection of cross section for comparison, Kriging interpolation was found to have the most similar configuration with the topographical configuration by showing the least difference in the area of cross section. Therefore, it is determined that the optimal modeling of reservoir bed with the water depth data measured by echo sounder shall provide basic information for efficient maintenance of reservoir.

• Journal of Korean Society for Geospatial Information Science
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• v.2 no.1 s.3
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• pp.93-98
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• 1994

This image of Kangseogu in Pusan, is a digital merge of aerial photos by scale of 1/1,200 map. The merge was carried out 2nd affine and bilinear interpolation. It can improve digital classification to help choose training sites and interprete classification results, and improve visual interpretation, as in this case, by adding detailed information to the multispectral TM data.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.931-931
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• 2012

제주지역의 강수자료는 최근에 이르러 69개 지점으로 증가하여 비교적 밀도있는 강수관측이 진행되고 있다. 그러나 기존의 자료 증설 내역과 이설 등으로 인해 과거로부터 현재에 이르는 자료를 기반으로 면적강수량을 산정할 경우 다소 어려움이 있다. 본 연구에서는 1992년부터 2010년까지의 강수자료를 바탕으로 관측소 개수를 기반으로 기간을 구분하여 각 기간별로 공간보간기법별로 면적강수량을 산정하고 이를 비교하였다. 사용한 공간보간기법은 PRISM(Parameter-elevation Regressions on Independent Slopes Model)기법과 티센(Thiessen)법으로 19년간의 일강수량 자료를 바탕으로 각각 면적강수량을 산정했다. PRISM기법을 이용한 경우는 고도, 관측점으로부터의 거리, 방향성 분석 및 해안가중치를 고려하여 계산하였고, 티센법의 경우는 기간별로 상이한 티센망을 구축하여 산정하였다. 지점 관측강수량에서 고도가 증가할수록 강수량이 증가하는 제주형 산악효과가 나타났으며 이는 보간기법에 의한 결과에서도 동일하게 나타나는 것으로 확인되었다. 또한 고도에 따른 상관성은 PRISM기법에 의한 결과에서 더 높게 산정되는 것으로 나타났다. 기법별 산정된 면적강수량은 근소한 차이를 보였으며 PRISM기법에 의한 값이 티센법에 비해 약 1%정도 크게 계산되었다.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.144-144
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• 2023

하천 합류부에 있어 수체의 혼합양상 분석은 고해상도의 자료가 필요하다. 하지만 최근 공간적 분포를 해석함에 있어 3D 기법들을 많이 활용되고 있다. IDW, Natural Neighbor, Kriging기법등 다양한 기법들이 많이 적용되고 있고 그에 따라 각 보간법을 비교 분석하여 공간해석에 대한 연구를 진행하였다. 관련 논문을 검토한 결과, 측정 결과에 따른 2차원 횡단면 분포의 내용이 지배적이었고, 3차원 매핑 및 3차원 분석을 통한 수리학적 정보 획득에 관한 연구는 부족한 실정이였다. 특히 3차원 하천 수질 농도의 연구가 불충분했다. 그에 따라 저해상도 측정결과에서의 예측과 보간법에 대한 시각화를 통해 하천의 전체적인 수리·수질정보를 표기하였다. 각각의 보간법을 비교함으로써 하천매핑에 있어 Kriging 기법을 적용하여 시각화된 자료와 정량적 평가를 통해 하천매핑의 정밀성을 향상시켰다. 하천합류부를 공간 분석할 시에 하천의 측정데이터에 대한 신뢰도를 바탕으로 계측경로에 따라 보간한 결과에 대한 신뢰도 분석을 실시하였다. 분석된 3차원자료를 이용하여 하천의 혼합거리에 대한 분석을 실시하였고 그에 따른 수표면과 연직방향까지 고려된 혼합거리분석을 비교하였다. 3차원 데이터를 활용하는 방법으로 측정 및 모니터링 기술의 중요한 데이터로 활용되며, 이러한 데이터는 유해물질 저감 기술 및 평가 예측 기술의 기초 데이터로 활용되고 있다. 유해화학물질 추정, 호수의 고위험 조류군 계층분석 등 다양한 수생건강 진단기술을 활용할 수 있다.

• Journal of Korea Multimedia Society
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• v.14 no.3
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• pp.339-347
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• 2011

As the volume visualization has been applied to render medical datasets, there has been a requirement to produce high quality images. Even though nice images can be generated by using previous linear filter, high order filter is required for better images. However, it takes much time for high order resampling, so that, overall rendering time is increased. In this paper, we perform high quality volume visualization using the cardinal interpolation. By enabling the empty space leaping which reduces the number of resampling, we achieve the efficient visualization. In detail, we divide the volume data into small blocks and leap empty blocks by referring the upper and lower bound value for each block. We propose a new method to estimate upper and lower bound value of for each block. As the result, we noticeably accelerated high quality volume visualization.

• The Journal of the Acoustical Society of Korea
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• v.28 no.2
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• pp.85-95
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• 2009

In the binaural synthesis environments, wide varieties of the head-related transfer functions (HRTFs) that have measured with a various direction would be desirable to obtain the accurate and various spatial sound images. To reduce the size' of HRTFs, interpolation has been often employed, where the HRTF for any direction is obtained by a limited number of the representative HRTFs. In this paper, we study on the distortion measures for interpolation, which has an important role in interpolation. With lhe various objective distortion metrics, the differences between the interpolated and the measured HRTFs were computed. These were then compared and analyzed with the results from the listening tests. From the results, the objective distortion measures were selected, that reflected the perceptual differences in spatial sound image. This measure was employed in a practical interpolation technique. We applied the proposed method to four kinds of an HRTF set, measured from three human heads and one mannequin. As a result, the Mel-frequency cepstral distortion was shown to be a good predictor for the differences in spatial sound location, when three HRTF measured from human, and the time-domain signal to distortion ratio revealed good prediction results for the entire four HRTF sets.

• Journal of the Korean Geotechnical Society
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• v.38 no.1
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• pp.5-15
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• 2022

Due to the Pohang earthquakes in 2017, concerns are increasing that Korea is no longer safe from liquefaction, and needs the research to take proper measures for liquefaction. Liquefaction is defined as the loss of shear strength of the ground. In order to solve this problem, many studies, such as composing a liquefaction hazard map using Liquefaction Potential Index (LPI), have been conducted. However, domestic researches on the comparative analysis of liquefaction prediction results are not sufficient. Therefore, in this study, liquefaction hazard maps were composed using the standard penetration test results, shear wave velocity values, and cone penetration test results. After that, the precision was determined by comparing the calculated LPI using the geotechnical information and predicted LPI via spatial interpolation target. Based on the analysis results, the predicted LPI value using geotechnical information is more precise than using calculated LPI value.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.71-72
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• 2019

본 논문에서는 계층구조 합성곱 신경망 기반의 고해상도 동영상 프레임 고속 보간 방법을 제안한다. 기존의 고해상도 동영상 프레임 보간 방법은 시간 해상도와 공간 해상도를 분리하여 보간 하기 때문에, 예측된 보간 프레임이 블러(blur) 열화를 갖는 문제를 보인다. 제안하는 방법에서는 이러한 문제를 해결하기 위하여 계층구조 합성곱 신경망 기반의 보간 방법을 이용한다. 제안하는 계층구조 합성곱 신경망은 우선 저해상도의 광학 흐름 추정지도를 생성하고 이를 고해상도로 복원하여 프레임 보간을 수행한다. 이때, 저해상도 광학 흐름 지도를 추정할 때 사용된 특징 정보들을 활용하여 고품질의 고해상도 광학 흐름 지도를 추정한다. 실험을 통하여 제안하는 방법이 고해상도 프레임을 고속으로 보간하며, 동시에 블러 열화에 대한 성능 향상을 가짐을 보였다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.86-94
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• 2010

In this paper, we propose spatially adaptive color demosaicing of noisy Bayer data. When sensor noises are not considered in demosaicing, they may degrade result image. In order to obtain high resolution image, sensor noises are considered in the color demosaicing step. We identify flat, edge and pattern regions at each pixel location to improve the performance of the algorithm and to reduce complexity. Based on the pre-classified regions, the demosaicing of the G channel is performed using the local statistics to reduce the interpolation error. The sensor noise is simultaneously removed by a modified version of non-local mean filter in the green and in the color difference domain. The R and B channels are interpolated easily using fully interpolated and denoised G and color difference values. Experimental results show that the proposed method achieves a significant improvement in terms of visual and numerical criteria, when compared to conventional methods.

• Journal of the Korea Computer Industry Society
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• v.4 no.10
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• pp.581-586
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• 2003

In this paper, we propose a region-based deinterlacing algorithm which is computationally efficient and shows effective visual performance. Computer simulation results indicate that the proposed algorithm shows better visual performance than conventional deinterlacing algorithms.