• The KIPS Transactions:PartB
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• v.14B no.5
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• pp.351-360
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• 2007

Video Completion refers to a computer vision technique which restores damaged images by filling missing pixels with suitable color in a video sequence. We propose a new video completion technique to fill in image holes which are caused by removing an unnecessary object in a video sequence, where two objects cross each other in the presence of camera motion. We remove the closer object from a camera which results in image holes. Then these holes are filled by color information of some others frames. First of all, spatio-temporal volumes of occluding and occluded objects are created according to the centroid of the objects. Secondly, a temporal search technique by voxel matching separates and removes the occluding object. Finally. these holes are filled by using spatial search technique. Seams on the boundary of completed pixels we removed by a simple blending technique. Experimental results using real video sequences show that the proposed technique produces new completed videos.

• 한국지구물리탐사학회:학술대회논문집
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• 2006.06a
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• pp.117-122
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• 2006

In the geophysical monitoring to understand the change of subsurface material properties with time, the time-invariant static subsurface model is commonly adopted to reconstruct a time-lapse image. This assumption of static model, however, can be invalid particularly when fluid migrates very quickly in highly permeable medium in the brine injection experiment. In such case, the resultant subsurface images may be severely distorted. In order to alleviate this problem, we develop a new least-squares inversion algorithm under the assumption that the subsurface model will change continuously in time. Instead of sampling a time-space model into numerous space models with a regular time interval, a few reference models in space domain at different times pre-selected are used to describe the subsurface structure continuously changing in time; the material property at a certain space coordinate are assumed to change linearly in time. Consequently, finding a space-time model can be simplified into obtaining several reference space models. In order to stabilize iterative inversion and to calculate meaningful subsurface images varying with time, the regularization along time axis is introduced assuming that the subsurface model will not change significantly during the data acquisition. The performance of the proposed algorithm is demonstrated by the numerical experiments using the synthetic data of crosshole dc resistivity tomography.

• Journal of Broadcast Engineering
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• v.17 no.6
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• pp.1048-1060
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• 2012

In this paper, an adaptive temporal and spatial filter (ATSF) based on mean square error (MSE) estimation is proposed. ATSF is a block based de-noising algorithm. Each noisy block is selectively filtered by a temporal filter or a spatial filter. Multi-hypothesis motion compensated filter (MHMCF) and bilateral filter are chosen as the temporal filter and the spatial filter, respectively. Although there is no original video, we mathematically derivate a formular to estimate the real MSE between a block de-noised by MHMCF and its original block and a linear model is proposed to estimate the real MSE between a block de-noised by bilateral filter and its original block. Finally, each noisy block is processed by the filter with a smaller estimated MSE. Simulation results show that our proposed algorithm achieves substantial improvements in terms of both visual quality and PSNR as compared with the conventional de-noising algorithms.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.556-566
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• 2001

This paper proposes a motion-adaptive de-interlacing algorithm based on EBMF(Edge Based Median Filter) and AMPDF(Adaptive Minimum Pixel Difference Fillet). To compensate 'motion missing'error, which is an important factor in motion-adaptive methods, we used AMPDF which estimates an accurate value using different thresholds after classifying the input image to 4 classes. To efficiently interpolate the moving diagonal edge, we also used EBMF which selects a candidate pixel according to the edge information. Finally, we, to increase the performance, adopted an adaptive interpolation after classifying the input image to moving region, stationary region, and boundary region. Simulation results showed that the proposed method provides better performance than the existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.5
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• pp.1019-1024
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• 2005

MPEG-2 achieves high compression radio, by exploiting the temporal and spatial correlations in real image sequence, using the motion compensated prediction and the transform coding, respectively. However, as the image sequence is more highly compressed, the encoded bitstream becomes more vulnerable to transmission error over the noisy channels. Furthermore, er개rs in the headers are fatal to decoding processes, because the header parameters in the video coding standard include a lot of important information connected to the syntax elements, fables, and decoding process. In this paper, we propose a new error resilience method using LSB coding for header parameters in MPEG-2 coded video transmissions. The experimental results for football and susie video sequence demonstrate that the proposed error resilience method for header parameters in MPEG-2 bitstream has good performance.

• Journal of Broadcast Engineering
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• v.13 no.3
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• pp.289-298
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• 2008

We propose an SNR-scalable coding algorithm for three-dimensional mesh sequences based on singular value decomposition (SVD). SVD achieves a coding gain by representing a mesh sequence with a small number of basis vectors and singular values. First, we introduce a bit plane coding scheme and derive a quantitative relationship between each bit plane and the reconstructed image quality. Using the relationship, we develop a rate-distortion (RD) optimized coding algorithm. Moreover, we propose prediction techniques to exploit the spatio-temporal correlations in real mesh sequences. Simulation results demonstrate that the proposed algorithm provides significantly better RD performance than conventional SVD coders.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.89-89
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• 2021

부영양화된 호수나 유속이 느린 하천에서 발생하는 녹조의 과도한 발생은 하천 생태계 훼손, 동식물의 건강, 담수의 오염 등 환경 사회 경제적으로 큰 피해를 준다. 현재 수질 측정망은 정해진 지점에서 Chlorophyll-a(Chl-a), Phycocyanin(PC)을 대표농도로 산정하고 조류경보에 활용하고 있으나, 일주일에 한번씩 샘플링을 통해 Chl-a 및 PC를 측정하여 시공간적인 신뢰성의 문제가 제기될 수 있다. 본 연구에서는 기존 점단위 조류 모니터링의 한계점을 개선하기 위해 초분광영상 자료를 머신러닝 기법에 적용하여 Chl-a 및 PC 산정 알고리즘을 개발하였다. 이를 위해 Chl-a와 PC의 최대 흡수, 반사 파장대, 주요 물 흡수 파장대 자료를 조합하여 9개의 파장비를 구축하였으며, 기존 연구에서 활용한 머신러닝 기법인 Partial Least Square, Random Forest, Gradient Boosting, Support Vector Machine, K-Nearest Neighbor, Artificial Neural Network를 검토하여 최적 모델을 선정하였다. 학습된 머신러닝의 성능을 R², NSE, RMSE 목적함수를 이용해 평가하였으며, 그 결과 ANN이 각각 PC 0.801, 0.755, 11.774 mg/m³, Chl-a 0.733, 0.622, 8.736 mg/m³로 가장 우수한 성능을 보였다. 최적화 된 ANN 모델을 백제보 상류 2016-2017년 항공 초분광영상에 적용하여 시공간에 따른 조류 분포변화를 평가하고자 한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1327-1333
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• 2018

Numerical analysis has the advantage that no actual flow pathways need to be formulated, making this technique especially useful for simulation analysis such as pathway design. However, it does require that the complete physical parameters of the fluid and the complete boundary conditions be known. If any of them are unknown, either the calculation will become impossible, or even if the calculation does converge, the reliability of the result will be low. Therefore, a means of more accurate acquisition of flow information is required. In this paper, we present techniques for estimating flow field from a constraint equation for image information and velocity field, based on the image intensity changes accompanying the motion of dye in waterway. In the equation, we entered a stabilizing term to suppress estimation error. We show the effectiveness of our method through experiments with generated and real images of a Karman vortex.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.202-202
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• 2023

전 세계적으로 지구 온난화로 인해 발생한 가뭄은 사회적, 경제적, 환경적으로 막대한 피해를 야기하고 있다. 국내의 경우, 2022년부터 현재까지 지속되고 있는 가뭄 상황은 강수의 지역적 편차로 인해 남부 지역 중심으로 극심한 피해가 발생하였다. 남부 지역의 주요 용수공급원인 영산강, 섬진강권역의 용수 공급율은 예년의 57%(3.8억 톤)에 불과하며, 일부 도서·산간 지역은 용수공급이 제한되는 현상까지 발생하였다. 이러한 가뭄 피해를 대비하기 위해 초기에 모니터링을 통한 선제적 대응 방안을 구축해야 한다. 가뭄 모니터링의 경우 미계측 지역에 대한 모니터링 방법으로 주기적이고 균질한 자료를 제공 받을 수 있는 위성영상을 활용한 연구가 수행되고 있다. 가뭄을 정량적으로 분석하고 판단하기 위해 가뭄지수를 활용하고 있으며, 대표적인 가뭄지수는 지상 관측강수량자료를 활용한 확률분포 기반의 표준강수지수 (Standardized Precipitation Index, SPI)와 강수 및 기온의 변동성이 포함된 표준강수증발산지수 (Standardized Precipitation Evapotranspiration Index, SPEI)가 있으며, 위성영상 자료를 활용한 가뭄지수인 증발스트레스지수(Evaporative Stress Index, ESI) 등이 있다. 본 연구에서는 강수와 기온을 고려한 가뭄지수인SPEI와 위성영상 기반의 가뭄지수인 ESI를 활용하여 2022년 남부 지역의 가뭄 사상을 중심으로 지표별 시공간적 변화를 분석하고자 한다. SPEI의 경우 기상관측소 지점자료의 기온과 강수량을 활용하였으며, Terra 위성의 MODIS (Moderate Resolution Imaging Spectroradiometer) 센서에서 제공되는 위성영상자료를 활용한 ESI는 미계측 지역에 대한 가뭄 판단을 위해 시·군별로 세분화하여 산정하였다.

• Journal of the Korean Society of Radiology
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• v.8 no.5
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• pp.231-240
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• 2014

The purpose of this study were to analyze that the Seoul neuropsychological screening battery (SNSB) for the evaluating cognitive assessment of the Parkinson's disease patients with mild cognitive impairment (PD-MCI) and the changes of the cerebral ventricle volume in the brain magnetic resonance imaging (MRI), and we has been bring forward the guideline to determine the diagnostic criteria for the PD-MCI. To achieve this, we was diagnosed with Parkinson's disease patients (PD-MCI group: 34 patients; Parkinson's disease with normal cognition, PD-NC group: 34 patients) to perform the SNSB test for the attention, language, memory, visuospatial, and frontal/executive functions and the brain MRI. Additionally, to compared the change of the cerebral ventricle volume, we performed the brain MRI for the 32 normal control (NC) group. The volumetric analysis for a specific cerebral ventricle performed by using Freesurfer Ver. 5.1 (Massachusetts general Hospital, Boston MA, USA). As a results, compared to the PD-NC group, the PD-MCI group were statistically significant reduction in the ability to perform the memory and the visuospatial function (p<0.05). The volumetric changes for a specific cerebral ventricle were statistically significant variation in the left and right lateral ventricle, left and right inferior lateral ventricle, and 3rd ventricle. Although, in order to compared the objectification, the normalized percentage applied to the volumetric changes showed to extend the PD-MCI group than the PD-NC group. Specially, the left and right ventricle extension for the PD-MCI patients conspicuously had showed a quantitative linear relationship between the memory and the visuospatial function for the SNSB (r>0.5, p<0.05). Therefore, we were able to judge the diagnostic criteria of the PD-MCI through that can observe the volumetric variation of the specific cerebral ventricle by using Freesurfer in brain MRI, and to analyze the correlation between the SNSB.