• 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.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.623-634
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• 2022

Due to river maintenance projects such as the creation of hydrophilic areas around rivers and the Four Rivers Project, the flow characteristics of rivers are continuously changing, and the risk of water quality accidents due to the inflow of various pollutants is increasing. In the event of a water quality accident, it is necessary to minimize the effect on the downstream side by predicting the concentration and arrival time of pollutants in consideration of the flow characteristics of the river. In order to track the behavior of these pollutants, it is necessary to calculate the diffusion coefficient and dispersion coefficient for each section of the river. Among them, the dispersion coefficient is used to analyze the diffusion range of soluble pollutants. Existing experimental research cases for tracking the behavior of pollutants require a lot of manpower and cost, and it is difficult to obtain spatially high-resolution data due to limited equipment operation. Recently, research on tracking contaminants using RGB drones has been conducted, but RGB images also have a limitation in that spectral information is limitedly collected. In this study, to supplement the limitations of existing studies, a hyperspectral sensor was mounted on a remote sensing platform using a drone to collect temporally and spatially higher-resolution data than conventional contact measurement. Using the collected spatio-temporal hyperspectral images, the tracer concentration was calculated and the transverse dispersion coefficient was derived. It is expected that by overcoming the limitations of the drone platform through future research and upgrading the dispersion coefficient calculation technology, it will be possible to detect various pollutants leaking into the water system, and to detect changes in various water quality items and river factors.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.275-292
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• 2022

In order to detect climate changes using satellite imagery, the GCOS (Global Climate Observing System) defines requirements such as spatio-temporal resolution, stability by the time change, and uncertainty. Due to limitation of GK-2A sensor performance, the level-2 products can not satisfy the requirement, especially for spatial resolution. In this paper, we found the optimal pan-sharpening algorithm for GK-2A products. The six pan-sharpening methods included in CS (Component Substitution), MRA (Multi-Resolution Analysis), VO (Variational Optimization), and DL (Deep Learning) were used. In the case of DL, the synthesis property based method was used to generate training dataset. The process of synthesis property is that pan-sharpening model is applied with Pan (Panchromatic) and MS (Multispectral) images with reduced spatial resolution, and fused image is compared with the original MS image. In the synthesis property based method, fused image with desire level for user can be produced only when the geometric characteristics between the PAN with reduced spatial resolution and MS image are similar. However, since the dissimilarity exists, RD (Random Down-sampling) was additionally used as a way to minimize it. Among the pan-sharpening methods, PSGAN was applied with RD (PSGAN_RD). The fused images are qualitatively and quantitatively validated with consistency property and the synthesis property. As validation result, the GSA algorithm performs well in the evaluation index representing spatial characteristics. In the case of spectral characteristics, the PSGAN_RD has the best accuracy with the original MS image. Therefore, in consideration of spatial and spectral characteristics of fused image, we found that PSGAN_RD is suitable for GK-2A products.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.9 s.351
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• pp.44-52
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• 2006

Recently developed MPEG-4 Part 2 compression standard provides a novel capability to handle arbitrary video objects. To support this capability, an efficient object segmentation technique is required. This paper proposes a real-time algorithm for foreground object segmentation in video sequences. The proposed algorithm consists of two steps: the first step that segments a video frame into multiple sub-regions using Spatio-Temporal Watershed Transform and the second step in which a foreground object segment is extracted from the sub-regions generated in the first step. For real-time processing, the algorithm is partitioned into hardware and software parts so that computationally expensive parts are off-loaded from a processor and executed by hardware accelerators. Simulation results show that the proposed implementation can handle QCIF-size video at 15 fps and extracts an accurate foreground object.

• Korean Journal of Remote Sensing
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• v.35 no.6_3
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• pp.1299-1312
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• 2019

As land remote sensing applications are expanding to the extraction of quantitative information, the importance of atmospheric correction is increasing. Considering the difficulty of atmospheric correction for land images, it should be applied when it is necessary. The quantitative information extraction and time-series analysis on biophysical variables in land surfaces are two major applications that need atmospheric correction. Atmospheric aerosol content and column water vapor, which are very dynamic in spatial and temporal domain, are the most influential elements and obstacles in retrieving accurate surface reflectance. It is difficult to obtain aerosol and water vapor data that have suitable spatio-temporal scale for high- and medium-resolution multispectral imagery. Selection of atmospheric correction method should be based on the availability of appropriate aerosol and water vapor data. Most atmospheric correction of land imagery assumes the Lambertian surface, which is not the case for most natural surfaces. Further BRDF correction should be considered to remove or reduce the anisotropic effects caused by different sun and viewing angles. The atmospheric correction methods of optical imagery over land will be enhanced to meet the need of quantitative remote sensing. Further, imaging sensor system may include pertinent spectral bands that can help to extract atmospheric data simultaneously.

• Journal of Broadcast Engineering
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• v.15 no.3
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• pp.321-331
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• 2010

Most of multimedia video coding algorithms are lossy schemes and several kinds of spatial and temporal artifacts are inevitable. Flickering, which is the most typical coding artifact in time domain, is mainly due to fact that the quality of coded sequence fluctuates as the quantization parameter is adjusted for rate control. In this paper, we analyzed the effect of quality variation according to the characteristics of video sequence when the I-frames are periodically inserted. And we proposed the FR(Full Reference)-based assessment algorithm to measure the amount of flickering artifacts in the coded video. It is discovered that the flickering becomes critical when the level of quality is intermediate and is affected by the amount of detail or movement, the size of object, and camera parameters. The proposed measurement algorithm shows is well consistent with HVS(Human Visual System).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.40-47
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• 2009

A motion adaptive video noise reduction scheme is proposed by cascading a temporal filter and a spatial filter. After a noise-robust motion detection is performed with a pre-spatial filter, the strength of the motion adaptive temporal filter is controlled by the amount of temporal movement. In order to fully utilize the temporal correlation of video signal, noisy input image is processed first by the temporal filter, therefore, image details of temporally stationary region are quite well preserved while undesired noises are suppressed. In contrast to the pre-spatial filter used for the robust motion detection, the cascaded post-spatial filter removes the remained noises by considering the strength of the temporal filter and the spatial self-similarity search results obtained from the pre-spatial filter.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.382-382
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• 2017

최근 전 세계적으로 가뭄 재해가 증가함에 따라 국내의 경우 가뭄상황을 모니터링하기 위하여 다양한 유관 기간에서 가뭄정보시스템을 활용하여 가뭄지수를 공간지도 형태로 제공하고 있다. 기상청 수자원공사 농어촌공사 등에서 기상/수문/농업관련 가뭄지수의 위험지도를 실시간으로 제공하고 있으며 각 지표별로 수문기상학적 특징과 용수공급시설 및 수요공급의 이수상황 등을 고려하여 활용하고 있다. 하지만 제공되고 있는 가뭄지수의 공간분포는 지점 자료를 기반으로 내삽기법 (interpolation)을 통해 재 산정된 지도로 공간 해상도 측면에서 조악한 해상도를 갖고 있다. 이와 같은 한계점을 보완하기 위하여 시 공간적으로 특성이 동일한 광범위한 지역에 대한 정보를 주기적으로 제공 가능하다는 측면에서 위성영상자료를 활용한 가뭄모니터링 연구의 필요성이 요구된다. 본 연구에서는 위성영상을 이용한 식생 정보 및 기후 정보 생물물리학적 정보를 활용한 식생가뭄반응지수 (Vegetation Drought Response Index in Korea VegDRI-Korea)를 제시하고 국내의 적용성 검증을 위하여 국내 주요 가뭄 사상을 대상으로 시공간적 가뭄상황을 분석하였다. 식생가뭄반응지수는 유역단위 또는 행정구역 단위별로 실시간 가뭄 상황을 분석할 수 있는 고해상도 위성영상 기반의 가뭄지수로써 향후 한반도 전역의 가뭄모니터링 및 주기적인 모니터링을 통해 가뭄예상지역 판단에 대한 의사결정지원에 활용할 수 있다.

• Information Systems Review
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• v.25 no.3
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• pp.121-138
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• 2023

The advancement in mobile technology brought disruptive innovation in media industry. The introduction of mobile devices broke spatial and temporal restrictions in media consumption. This study investigates the impact of mobile channel adoption on video viewing behavior, using real-world dataset obtained from a particular on-demand service provider in South Korea. We find that the adoption of a mobile channel significantly increases the total viewing time of video-on-demand via TV and the number of contents viewed. Our results suggest that the mobile channels act as a complement channel to conventional TV channels. We provide theoretical and practical insights on consumer usage in the emerging over-the-top market.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.113-121
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• 2012

In this paper, we proposed fast and efficient algorithm for detecting near-duplication based on content based retrieval in large scale video database. For handling large amounts of video easily, we split the video into small segment using scene change detection. In case of video services and copyright related business models, it is need to technology that detect near-duplicates, that longer matched video than to search video containing short part or a frame of original. To detect near-duplicate video, we proposed motion distribution and frame descriptor in a video segment. The motion distribution descriptor is constructed by obtaining motion vector from macro blocks during the video decoding process. When matching between descriptors, we use the motion distribution descriptor as filtering to improving matching speed. However, motion distribution has low discriminability. To improve discrimination, we decide to identification using frame descriptor extracted from selected representative frames within a scene segmentation. The proposed algorithm shows high success rate and low false alarm rate. In addition, the matching speed of this descriptor is very fast, we confirm this algorithm can be useful to practical application.