• Nuclear Engineering and Technology
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• 제54권6호
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• pp.2204-2212
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• 2022

Recently, the demand for alpha imaging detectors for quantifying the distributions of alpha particles has increased in various fields. This study aims to reconstruct a high-resolution image from an alpha imaging detector by applying a super-spatial resolution method combined with the maximum-likelihood expectation maximization (MLEM) algorithm. To perform the super-spatial resolution method, several images are acquired while slightly moving the detector to predefined positions. Then, a forward model for imaging is established by the system matrix containing the mechanical shifts, subsampling, and measured point-spread function of the imaging system. Using the measured images and system matrix, the MLEM algorithm is implemented, which converges towards a high-resolution image. We evaluated the performance of the proposed method through the Monte Carlo simulations and phantom experiments. The results showed that the super-spatial resolution method was successfully applied to the alpha imaging detector. The spatial resolution of the resultant image was improved by approximately 12% using four images. Overall, the study's outcomes demonstrate the feasibility of the super-spatial resolution method for the alpha imaging detector. Possible applications of the proposed method include high-resolution imaging for alpha particles of in vitro sliced tissue and pre-clinical biologic assessments for targeted alpha therapy.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.648-650
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• 2003

Efficient multi-resolution image fusion aims to take advantage of the high spectral resolution of Landsat TM images and high spatial resolution of SPOT panchromatic images simultaneously. This paper presents a multi-resolution data fusion scheme, based on multirate image representation. Motivated by analytical results obtained from high-resolution multispectral image data analysis: the energy packing the spectral features are distributed in the lower frequency bands, and the spatial features, edges, are distributed in the higher frequency bands. This allows to spatially enhancing the multispectral images, by adding the high-resolution spatial features to them, by a multirate filtering procedure. The proposed method is compared with some conventional methods. Results show it preserves more spectral features with less spatial distortion.

• 대한원격탐사학회지
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• 제22권5호
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• pp.337-350
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• 2006

The characteristics of neighborhood correlation images for change detection were explored at different spatial resolution scales. Bi-temporal QuickBird datasets of Las Vegas, NV were used for the high spatial resolution image analysis, while bi-temporal Landsat $TM/ETM^{+}$ datasets of Suwon, South Korea were used for the mid spatial resolution analysis. The neighborhood correlation images consisting of three variables (correlation, slope, and intercept) were evaluated and compared between the two scales for change detection. The neighborhood correlation images created using the Landsat datasets resulted in somewhat different patterns from those using the QuickBird high spatial resolution imagery due to several reasons such as the impact of mixed pixels. Then, automated binary change detection was also performed using the single and multiple neighborhood correlation image variables for both spatial resolution image scales.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.153-153
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• 2022

Large-scale and accurate observations at fine spatial resolution through a means of remote sensing offer an effective tool for capturing rainfall variability over the traditional rain gauges and weather radars. Although satellite rainfall products (SRPs) derived using two major estimation approaches were evaluated worldwide, their practical applications suffered from limitations. In particular, the traditional top-down SRPs (e.g., IMERG), which are based on direct estimation of rain rate from microwave satellite observations, are mainly restricted with their coarse spatial resolution, while applications of the bottom-up approach, which allows backward estimation of rainfall from soil moisture signals, to novel high spatial resolution soil moisture satellite sensors over South Korea are not introduced. Thus, this study aims to evaluate the performances of a state-of-the-art bottom-up SRP (the self-calibrated SM2RAIN model) applied to the C-band SAR Sentinel-1, a statistically downscaled version of the conventional top-down IMERG SRP, and their integration for a targeted high spatial resolution of 0.01° (~ 1-km) over central South Korea, where the differences in climate zones (coastal region vs. mainland region) and vegetation covers (croplands vs. mixed forests) are highlighted. The results indicated that each single SRP can provide plus points in distinct climatic and vegetated conditions, while their drawbacks have existed. Superior performance was obtained by merging these individual SRPs, providing preliminary results on a complementary high spatial resolution SRP over central South Korea. This study results shed light on the further development of integration framework and a complementary high spatial resolution rainfall product from multi-satellite sensors as well as multi-observing systems (integrated gauge-radar-satellite) extending for entire South Korea, toward the demands for urban hydrology and microscale agriculture.

• 대한원격탐사학회지
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• 제16권1호
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• pp.87-98
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• 2000

상업위성에서 공급되는 고해상도영상의 활용을 증대하기 위한 영상합성에 대한 관심이 증가하고 있다. 합성에 사용된 고해상도 흑백영상과 저해상도 다중분광영상은 항공기탑재 다중분광 주사기에 의해 촬영된 네 밴드의 영상을 이용하여 모의 제작하였다. 모의 합성된 2rl 해상도의 흑백 영상과 Bnl 해상도의 네 밴드 영상에 대하여 다섯 가지 합성방법(MWD, ItIS, PCA, HPF, CN, PCA) 을 적용하였다. 합성된 영상에 대해서 원래 영상들이 가지고 있던 공간해상도와 분광정보 측면의 특성을 분석하고자, 육안판독, 통계치비교, semivariogram, 분광반사특성 등을 비교하였다. MWD 변환방법에 의하여 합성된 영상이 공간해상도 및 분광정보 측면에서 모두 합성에 사용된 원래 영상과 근접한 결과를 보였다.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2008년도 International Meeting on Information Display
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• pp.859-862
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• 2008

We present a new tool to measure precisely the emissive properties of displays at the pixel level with submicrometric spatial resolution. It is useful to check the technological defects and their impact on the emissive properties of the displays. Backlight films and transflective and reflective displays are measured.

• 대한공간정보학회지
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• 제22권1호
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• pp.23-29
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• 2014

고해상도 위성영상의 등장과 공간분해능의 발전은 위성영상을 활용한 다양한 연구들을 가능하게 하였다. 그 중에서도 고해상도 위성영상을 이용한 표적 탐지 기술은 광범위한 지역의 차량, 항공기, 선박 등의 탐지를 가능하게 하여 교통류 모델링, 군사적 목적의 감시 정찰을 효과적으로 수행하게 한다. 최근 다양한 국가에서 여러 위성을 발사함에 따라 위성영상 선택의 폭이 증가하였으나 고해상도 위성영상을 이용한 공간해상도 비교 연구는 많지 않으며 더욱이 표적 탐지에 미치는 공간 해상도의 영향에 관한 연구는 국내외로 매우 부족한 상황이다. 따라서 본 연구에서는 PSO 기반의 표적 탐지 연구를 바탕으로 공간해상도가 항공기 및 선박 표적 탐지에 미치는 영향을 분석하였다. 원영상에 대한 재배열 보간 기법을 통해 0.5m, 1m, 2m, 4m의 다양한 공간해상도의 시뮬레이션 영상을 생성하고 이때 최근린보간, 양선형보간, 3차회선보간과 같이 다양한 재배열 보간 기법을 적용하였다. 표적 탐지 정확도는 공간해상도 뿐만 아니라 보간 기법에 따라 비교 분석되었다. 연구 결과 0.5m의 고해상도 영상에서 그리고 최근린보간 기법을 이용한 재배열 영상에서 더 높은 표적 탐지 정확도를 얻을 수 있음을 확인하였다. 또한 50% 이상의 표적 탐지 정확도를 얻기 위해서는 항공기의 경우 2m, 선박의 경우 4m 이상의 영상이 필요하며 항공기의 형태적 특이성은 더 높은 공간 해상력을 필요로 함을 확인하였다. 본 연구는 항공기 및 선박 표적 탐지에 적합한 적정 공간분해능을 제안하고 위성 센서 설계의 기준을 제시하는데 큰 기여를 할 것으로 사료된다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.115-118
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• 2004

Images with high resolution are desired and often required in many visual applications. When resolution can not be improved by replacing sensors, either because of cost or hardware physical limits, super resolution image reconstruction method is what can be resorted to. Super resolution image reconstruction method refers to image processing algorithms that produce high quality and high resolution images from a set of low quality and low resolution images. The method is proved to be useful in many practical cases where multiple frames of the same scene can be obtained, including satellite imaging, video surveillance, video enhancement and restoration, digital mosaicking, and medical imaging. The method can be either the frequency domain approach or the spatial domain approach. Much of the earlier works concentrated on the frequency domain formulation, but as more general degradation models were considered, later researches had been almost exclusively on spatial domain formulations. The method in spatial domains has three stages: i) motion estimate or image registration, ii) interpolation onto high resolution grid and iii) deblurring process. The super resolution grid construction in the second stage was discussed in this paper. We applied the Maximum A­Posteriori(MAP) reconstruction method that is one of the major methods in the super resolution grid construction. Based on this method, we reconstructed high resolution images from a set of low resolution images and compared the results with those from other known interpolation methods.

• 한국컴퓨터그래픽스학회논문지
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• 제25권3호
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• pp.21-29
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• 2019

본 논문에서는 구조-텍스처 분할 기법을 기반으로 위성영상을 분할 융합하여 공간 해상도를 개선시키는 프레임워크를 제시한다. 위성영상은 센서가 감지하는 파장에 따라 다양한 공간해상도를 가진다. 전정 영상 (panchromatic image)은 일반적으로 높은 공간해상도를 가지지만 단일 흑백컬러를 가지고 있는 반면, 다중분광 영상 (multi-spectral image)나 적외선 영상은 전정 영상에 비해 낮은 공간해상도를 가지지만 다양한 분광 밴드정보와 열 정보를 가지고 있다. 본 논문에서는 다중분광 영상이나 적외선 영상의 공간 해상도를 향상시키기 위해 영상의 디테일이 텍스처 영상에만 존재한다는 것에 착안하여 본 프레임워크를 고안하였다. 고안된 프레임워크에서는 저해상도 영상과 고해상도 영상이 구조 영상과 텍스처 영상으로 분할된 뒤, 저해상도 구조영상은 고해상도 구조 영상을 참조하여 가이디드 필터링 된다. 구조-텍스처 영상 모델에 따라 필터링된 저해상도 영상의 구조 영역과 고해상도 영상의 텍스처 영역을 픽셀 단위로 더해져서 최종 영상이 생성된다. 생성된 영상은 저해상도 영상의 밴드와 고해상도 영상의 디테일을 포함한다. 제시하는 방법은 분광해상도와 공간해상도를 모두 보존할 수 있음을 실험적으로 확인하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.525-527
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• 2003

Recently, the spatial resolution of earth observation satellites is significantly increased to a few meters. Such high spatial resolution images definitely will provide lots of information for detail-thirsty remote sensing users. However, it is more difficult to develop automated image algorithms for automated image feature extraction and pattern recognition. In this study, we propose a two-stage procedure to extract road information from high resolution satellite images. At first stage, a watershed segmentation technique is developed to classify the image into various regions. Then, a knowledge is built for road and used to extract the road regions. In this study, we use panchromatic and multi-spectral images of the IKONOS satellite as test dataset. The experiment result shows that the proposed technique can generate suitable and meaningful road objects from high spatial resolution satellite images. Apparently, misclassified regions such as parking lots are recognized as road needed further refinement in future research.