• 천문학회보
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• 제44권2호
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• pp.78.1-78.1
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• 2019

There are a huge number of faint objects that have not been observed due to the lack of large and deep surveys. In this study, we demonstrate that a deep learning approach can produce a better quality deep image from a single pass imaging so that could be an alternative of conventional image stacking technique or the expensive large and deep surveys. Using data from the Sloan Digital Sky Survey (SDSS) stripe 82 which provide repeatedly scanned imaging data, a training data set is constructed: g-, r-, and i-band images of single pass data as an input and r-band co-added image as a target. Out of 151 SDSS fields that have been repeatedly scanned 34 times, 120 fields were used for training and 31 fields for validation. The size of a frame selected for the training is 1k by 1k pixel scale. To avoid possible problems caused by the small number of training sets, frames are randomly selected within that field each iteration of training. Every 5000 iterations of training, the performance were evaluated with RMSE, peak signal-to-noise ratio which is given on logarithmic scale, structural symmetry index (SSIM) and difference in SSIM. We continued the training until a GAN model with the best performance is found. We apply the best GAN-model to NGC0941 located in SDSS stripe 82. By comparing the radial surface brightness and photometry error of images, we found the possibility that this technique could generate a deep image with statistics close to the stacked image from a single-pass image.

• 한국멀티미디어학회논문지
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• 제15권1호
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• pp.166-178
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• 2012

감성 세대로의 진입에 따라 소비자들의 선호 색을 반영한 자동차 선호 색상을 개발하려는 연구가 진행되고 있다. 본 연구에서는 제품 디자인과 소비 심리에 영향을 줄 수 있는 계층별 선호색과 감성 이미지에 의한 자동차 색에 대하여 조사 하였다. 조사 대상은 연령대 별, 성별에 따라 남, 여 20대, 30대, 40대, 50대 이상을 기준으로 8분류로 나누어 각각 30명씩 실시하였다. 선호 색상은 검은색, 흰색, 하늘색, 보라색, 분홍색, 주황색 순으로 나타났으며 검은색, 흰색, 회색을 제외한 색상은 파란색, 노란색, 보라색 순으로 나타났다. 감성적인 자동차 색상을 색상으로 보여주었을 때와 색상으로 보여주지 않았을 때 차이가 있음을 알 수 있었다. 이는 좋아하는 색상은 감성에 따르고 있으나 실제로 자동차 이미지가 보수적으로 인식되어 밝은 유채색 차의 선택을 주저하고 있음을 보여준다. 즉 아직은 감정표출에 있어 소극적임을 보여주고 있는 것이다.

• 전자공학회논문지CI
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• 제48권1호
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• pp.1-7
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• 2011

3차원 지도(3D Map)를 구축하기 위해서는 지형정보와 지도상에서 건물 영역 및 건물 형상 정보가 필요하다. 이를 위해 본 논문에서는 개선된 스네이크(Snake) 알고리즘으로 건물 영역을 반자동으로 추출하는 방법을 제안한다. 본 방법은 전처리, 제어점의 초기화, 개선된 스네이크 알고리즘 적용 세 단계로 구성한다. 첫 번째 단계에서는 위생영상을 그레이 영상으로 변환 후 근사 에지를 추출하여 그레이 영상과 합성한다. 두 번째 단계에서는 사용자가 건물의 중심점을 설정한 후 원형 또는 사각형 모양의 초기 제어점을 계산하여 설정한다. 세번째 단계에서는 개선된 스네이크 알고리즘을 적용하여 건물영역을 추출한다. 이러한 과정에서 스네이크 에너지 계산식의 한 항을 새로운 방법으로 설정하여 건물영역 추출용으로 특화하였다. 그리고 스카이 뷰의 위성영상을 이용하여 제안된 방법을 건물영역 매칭율을 평가하였는데 75%의 매칭율을 보였다.

• 한국지구과학회지
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• 제36권4호
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• pp.330-340
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• 2015

본 연구에서는 CCD 카메라가 장착된 Skyviewer로부터 촬영된 하늘 영상 자료를 이용하여 전운량을 산출하는 알고리즘을 개발하였다. 전운량 산출은 RGB 영상 내의 차폐 영역을 제거하고 GBR 빈도분포에 따른 영상을 분류하며, RBR 경계값을 결정하여 구름 화소를 분류한다. 분류된 구름 화소에서 태양광 영역을 제거한 후 유효성 검사를 통해 전운량을 산출하게 된다. 전운량 산출 알고리즘의 정확성을 검증하기 위하여 관측소와 가장 가까운 강원지방기상청의 목측 전운량 자료와 편이(Bias), 평균제곱근오차(RMSE), 상관계수를 분석하였다. 선정된 사례는 계절별 일 사례로 8시부터 17시까지의 정시 자료를 사용하였다. 분석 결과 Skyviewer로부터 산출된 전운량의 편이는 평균적으로 -0.8할의 차이를 보였으며, 평균제곱근오차는 1.6할로 전운량의 차이가 2할 내에서 나타나고 있었다. 또한, 두 관측소는 떨어진 거리의 차이가 있음(약 4 km)에도 불구하고 상관계수가 모든 사례에서 평균 0.91 이상으로 매우 높았다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4419-4441
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• 2016

A cause of vehicle accidents is the reduced visibility due to bad weather conditions such as fog. Therefore, an onboard vision system should take visibility detection into account. In this paper, we propose a simple and effective approach for measuring the visibility distance using a single camera placed onboard a moving vehicle. The proposed algorithm is controlled by a few parameters and mainly includes camera parameter estimation, region of interest (ROI) estimation and visibility computation. Thanks to the ROI extraction, the position of the inflection point may be measured in practice. Thus, combined with the estimated camera parameters, the visibility distance of the input foggy image can be computed with a single camera and just the presence of road and sky in the scene. To assess the accuracy of the proposed approach, a reference target based visibility detection method is also introduced. The comparative study and quantitative evaluation show that the proposed method can obtain good visibility detection results with relatively fast speed.

• Journal of Astronomy and Space Sciences
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• 제20권4호
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• pp.403-416
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• 2003

There are common features, in both imaging surveys and image processing, between astronomical observations and remote sensing. Handling large amounts of data, in an easy and fast way, has become a common issue. Implementing pipeline software can be a solution to the problem, one which allows the processing of various kinds of data automatically. As a case study, the development of pipeline software for the EIS (European Southern Observatory Imaging Survey) is introduced. The EIS team has been conducting a sky survey to provide candidate targets to the 250 VLTs (Very Large Telescopes) observations. The survey data have been processed in a sequence of five major data corrections and reductions, i.e. preprocessing, flat fielding, photometric and astrometric corrections, source extraction, and coaddition. The processed data are eventually distributed to the users. In order to provide automatic processing of the vast volume of observed data, pipeline software has been developed. Because of the complexity of objects and different characteristic of each process, it was necessary to analyze the whole works of the EIS survey program. The overall tasks of the EIS are identified, and the scheme of the EIS pipeline software is defined. The system structure and the processes are presented, and in-depth flow charts are analyzed. During the analyses, it was revealed that handling the data flow and managing the database are important for the data processing. These analyses may also be applied to many other fields which require image processing.

• 항공우주기술
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• 제11권2호
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• pp.164-170
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• 2012

본 논문에서는 SAR 영상 내부에서 나타나는 능동 트랜스폰더의 응답으로부터 얻은 위치정보와 GPS 장비를 이용하여 획득한 위치정보를 비교한 후, 능동 트랜스폰더의 지상기준점(GCP) 활용 가능성에 대한 연구를 수행하였다. 신호대 클러터 비(SCR)를 향상시키기 위하여 X밴드 대역의 중심주파수를 가지는 능동 트랜스폰더는 넓고 평평한 지역에 설치되었으며, 능동 트랜스폰더의 응답을 얻기 위하여 Cosmo-SkyMed 영상이 사용되었다. 이후 위치정확도 측정을 위하여 SAR 영상 내부와 GPS 장비로부터 측정된 능동 트랜스폰더의 위치정보를 비교하였으며, ENVI-SARscape 소프트웨어가 SAR 영상 내부에서의 능동 트랜스폰더 위치정보를 얻기 위하여 사용되었다. 이러한 비교분석을 통하여 본 논문에서는 능동 트랜스폰더의 응답이 SAR 영상의 지상기준점 응답으로 적절하다는 것을 보이고자 한다.

• 대기
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• 제29권5호
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• pp.537-550
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• 2019

To analyze the observation environment of solar radiation stations operated by the Korea Meteorological Administration (KMA), we analyzed the skyline, Sky View Factor (SVF), and solar radiation due to the surrounding topography and artificial structures using a Digital Elevation Model (DEM), 3D camera, and solar radiation model. Solar energy shielding of 25 km around the station was analyzed using 10 m resolution DEM data and the skyline elevation and SVF were analyzed by the surrounding environment using the image captured by the 3D camera. The solar radiation model was used to assess the contribution of the environment to solar radiation. Because the skyline elevation retrieved from the DEM is different from the actual environment, it is compared with the results obtained from the 3D camera. From the skyline and SVF calculations, it was observed that some stations were shielded by the surrounding environment at sunrise and sunset. The topographic effect of 3D camera is therefore more than 20 times higher than that of DEM throughout the year for monthly accumulated solar radiation. Due to relatively low solar radiation in winter, the solar radiation shielding is large in winter. Also, for the annual accumulated solar radiation, the difference of the global solar radiation calculated using the 3D camera was 176.70 MJ (solar radiation with 7 days; suppose daily accumulated solar radiation 26 MJ) on an average and a maximum of 439.90 MJ (solar radiation with 17.5 days).

• 천문학논총
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• 제30권2호
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• pp.595-597
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• 2015

LMC X-4 is an eclipsing high-mass X-ray binary exhibiting a superorbital modulation with a period of ~ 30:5 days. We present a detailed study of the variations of the superorbital modulation period with a time baseline of ~ 18 years. The period determined in the light curve collected by the Monitor of All-sky X-ray Image (MAXI) significantly deviates from that observed by the All Sky Monitor (ASM) onboard the Rossi X-ray Timing Explorer (RXTE). Using the data collected by RXTE/ASM, MAXI, and the Burst Alert Telescope (BAT) onboard Swift, we found a significant period derivative, $\dot{P}=(2.08{\pm}0.12){\times}10^{-5}$. Furthermore, the O{C residual shows complex short-term variations indicating that the superorbital modulation of LMC X-4 exhibits complicated unstable behaviors. In addition, we used archive data collected by the Proportional Counter Array (PCA) on RXTE to estimate the orbital and spin parameters. The detected pulse frequencies obtained in small time segments were fitted with a circular orbital Doppler shift model. In addition to orbital parameters and spin frequency for each observation, we found a spin frequency derivative of $\dot{v}=(6.482{\pm}0.011){\times}10^{-13}Hz{\cdot}s^{-1}$. More precise orbital and spin parameters will be evaluated by the pulse arrival time delay technique in the future.

• 대한원격탐사학회지
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• 제16권4호
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• pp.305-313
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• 2000

A vicarious calibration method was developed for the OSMI sensor calibration. Employing measured aerosol optical thickness by a sunphotometer and a sky radiometer and water leaving radiance by ship measurements as inputs, TOA (top of the atmosphere) radiance at each OSMI band was simulated in conjunction with a radiative transfer model (Rstar5b) by Nakajima and Tanaka (1988). As a case of examining the accuracy of this method, we simulated TOA radiance based on water leaving radiance measured at NASA/MOBY site and aerosol optical thickness estimated nearby at Lanai, and compared simulated results with SeaWiFS-estimated TOA radiances. The difference falls within about $\pm$5%, suggesting that OMSI sensor can be calibrated with the suggested accuracy. In order to apply this method for the OSMI sensor calibration, ground-based sun photometry and ship measurements were carried out off the east coast of Korean peninsula on May 31, 2000. Simulations of TOA radiance by using these measured data as input to the radiative transfer model show that there are substantial differences between simulated and OSMI-estimated radiances. Such a discrepancy appears to be mainly due to the cloud contamination because satellite image indicates optically thin clouds over the experimental area. Nevertheless results suggest that sensor calibration can be achieved within 5% uncertainty range if there are ground-based measurements of aerosol optical thickness, and water leaving radiances under clear-sky and optically thin atmospheric conditions.