• 한국측량학회지
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• 제28권4호
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• pp.421-430
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• 2010

영상분할은 관심대상이 되는 물체의 영역을 추출하기 위한 객체기반 영상분류의 전처리과정으로서 원격탐사 영상분석에서 그 중요성 날로 커지고 있다. 본 연구에서는 개선된 SRG(Seeded Region Growing) 기법과 영역병합과정을 이용하여 고해상도 영상분할을 위한 새로운 방법을 제안한다. 이를 위해 우선 QuickBird 융합영상에서 추출된 다중분광 에지정보를 이용하여 초기 시드포인트를 자동으로 추출하였다. 추출된 시드포인트에 영상의 기하학적인 정보와 분광정보를 반영할 수 있는 개선된 SRG 기법을 적용하여 초기 영상 분할을 수행하였다. 최종적으로 앞선 초기분할 결과 향상을 위해 분할된 영역의 평균분광정보를 활용하여 영역병합을 수행하여 최종분할결과를 도출하였다. 제안된 기법의 효율성을 평가하기 위해 무감독 영상분할 평가측정치를 이용하여 정확도 평가를 수행하였다. 실험결과 제안한 기법은 고해상도 영상분할에 유용하게 적용될 수 있으리라 판단된다.

• 대한원격탐사학회지
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• 제21권3호
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• pp.173-188
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• 2005

The present study aims to derive and compare narrow and broad bandwidths of ocean color sensor’s algorithms for the study of monitoring highly dynamic coastal oceanic environmental parameters using high-resolution imagery acquired from Multi-spectral Camera (MSC) on KOMPSAT-2. These algorithms are derived based on a large data set of remote sensing reflectances ($R_{rs}$) generated by using numerical model that relates $b_b/(a + b_b)$ to $R_{rs}$ as functions of inherent optical properties, such as absorption and backscattering coefficients of six water components including water, phytoplankton (chl), dissolved organic matter (DOM), suspended sediment (SS) concentration, heterotropic organism (he) and an unknown component, possibly represented by bubbles or other particulates unrelated to the first five components. The modeled $R_{rs}$ spectra appear to be consistent with in-situ spectra collected from Korean waters. As Kompsat-2 MSC has similar spectral characteristics with Landsat-5 Thematic Mapper (TM), the model generated $R_{rs}$ values at 2 ㎚ interval are converted to the equivalent remote sensing reflectances at MSC and TM bands. The empirical relationships between the spectral ratios of modeled $R_{rs}$ and chlorophyll concentrations are established in order to derive algorithms for both TM and MSC. Similarly, algorithms are obtained by relating a single band reflectance (band 2) to the suspended sediment concentrations. These algorithms derived by taking into account the narrow and broad spectral bandwidths are compared and assessed. Findings suggest that there was less difference between the broad and narrow band relationships, and the determination coefficient $(r^2)$ for log-transformed data [ N = 500] was interestingly found to be $(r^2)$ = 0.90 for both TM and MSC. Similarly, the determination coefficient for log-transformed data [ N = 500] was 0.93 and 0.92 for TM and MSC respectively. The algorithms presented here are expected to make significant contribution to the enhanced understanding of coastal oceanic environmental parameters using Multi-spectral Camera.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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• pp.301-306
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• 1998

Korea Aerospace Research Institute (KARI) is developing a Korea Multi-Purpose Satellite I (KOMPSAT-I) which accommodates Electro-Optical Camera (EOC), Ocean Scanning Multi-spectral Imager (OSMI), and Space Physics Sensor (SPS). The satellite has the weight of about 500kg and will be operated on the 10:50 AM sun-synchronized orbit with the altitude of 685 km. The satellite will be launched in 1999 and its lifetime is expected to be over 3 years. The main mission of EOC is the cartography to provide the images from a remote earth view for the production of 1/25000-scale maps of KOREA. EOC collects 510 ~ 730 nm panchromatic imagery with the ground sample distance(GSD) of 6.6 m and the swath width of 17 km by push broom scanning. EOC also can scan $\pm$45 degree across the ground track using body pointing method. The primary mission of OSMI is worldwide ocean color monitoring for the study of biological oceanography. It will generate 6 band ocean color images with 800 km swath width and 1km GSD by whiskbroom scanning. OSMI is designed to provide on-orbit spectral band selectability in the spectral range from 400 nm to 900 nm through ground command. This flexibility in band selection can be used for various applications and will provide research opportunities to support the next generation sensor design. SPS consists of High Energy Particle Detector (HEPD) and ionosphere Measurement Sensor (IMS). HEPD has missions to characterize the low altitude high-energy Particle environment and to study the effects of radiation environment on microelectronics. IMS measures densities and temperature of electrons in the ionosphere and monitors the ionospheric irregularities at the KOMPSAT orbit.

• International Journal of Computer Science & Network Security
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• 제23권1호
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• pp.1-10
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• 2023

Open surface water body extraction is gaining popularity in recent years due to its versatile applications. Multiple techniques are used for water detection based on applications. Different applications of Radar as LADAR, Ground-penetrating, synthetic aperture, and sounding radars are used to detect water. Shortwave infrared, thermal, optical, and multi-spectral sensors are widely used to detect water bodies. A stereo camera is another way to detect water and different methods are applied to the images of stereo cameras such as deep learning, machine learning, polarization, color variations, and descriptors are used to segment water and no water areas. The Satellite is also used at a high level to get water imagery and the captured imagery is processed using various methods such as features extraction, thresholding, entropy-based, and machine learning to find water on the surface. In this paper, we have summarized all the available methods to detect water areas. The main focus of this survey is on water detection especially in small patches or in small areas. The second aim of this survey is to detect water hazards for unmanned vehicles and off-sure navigation.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.791-793
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• 2006

In the satellite camera, the incoming light source is converted to electronic analog signals by the electronic component for example CCD (Charge Coupled Device) detectors. The analog signals are amplified, biased and converted into digital signals (pixel data stream) in the video processor (A/Ds). The outputs of the A/Ds are digitally multiplexed and driven out using differential line drivers (two pairs of wires) for cross strap requirement. The MSC (Multi-Spectral Camera) in the KOMPSAT-2 which is a LEO spacecraft will be used to generate observation imagery data in two main channels. The MSC is to obtain data for high-resolution images by converting incoming light from the earth into digital stream of pixel data. The video data outputs are then MUXd, converted to 8 bit bytes, serialized and transmitted to the NUC (Non-Uniformity Correction) module by the Hotlink data transmitter. In this paper, the video data streams, the video data format, and the image data processing routine for satellite camera are described in terms of satellite camera control hardware. The advanced satellite with very high resolution requires faster and more complex image data chain than this algorithm. So, the effective change of the used image data chain and the fast video data transmission method are discussed in this paper

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 춘계학술대회 논문집
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• pp.14-19
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• 2007

2차원 웨이블릿이나 3차원 웨이블릿 변환은 주파수 방향으로 나타나는 분광특성을 고려할 수 있는 장점이 있다. 그러나 다중분광 영상에서 3차원 웨이블릿 변환을 이용하여 분류한 연구사례는 발표되거나 보고된 사례가 거의 없다. 따라서 본 연구에서는 기존의 전통적인 분류기법에 의한 처리결과를 제시하고 3차원 웨이블릿 변환 계수와 에너지 변수량들을 이용한 분류 처리결과를 분류 정확도 측면에서 비교하여 분석하였다. 3D 웨이블릿의 경우 공간적인 변화양상과 주파수에 따른 분광정보의 변화 양상을 동시에 알려주는 계수로 표현되기 때문에 본 연구의 처리 기법은 다양한 분광특성을 지니는 객체들이 조밀하고 복합적으로 구성되어 있는 도시지역의 고 해상도 위성영상자료에 효과적으로 적용될 수 있다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.72-75
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• 2008

Image segmentation techniques becoming increasingly important in the field of remote sensing image analysis in areas such as object oriented image classification. This paper presents a new method for image segmentation in High Resolution Remote Sensing Image based on Seeded Region Growing (SRG) and Edge Information. Firstly, multi-spectral edge detection was done using an entropy operator in pan-sharpened QuickBird imagery. Then, the initial seeds were automatically selected from the obtained edge map. After automatic selection of significant seeds, an initial segmentation was achieved by applying SRG. Finally the region merging process, using region adjacency graph (RAG), was carried out to get the final segmentation result. Experimental results demonstrated that the proposed method has good potential for application in the segmentation of high resolution satellite images.

• 한국지리정보학회지
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• 제15권3호
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• pp.66-80
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• 2012

원격탐사 방법을 활용한 변화지역 탐지, 재난재해 지도 작성, 작황 모니터링 등 다중시기의 위성영상을 활용한 결과를 도출하기 위해서는 시계열 영상 정보를 서로 비교할 수 있는 공통의 스케일로 정규화 하는 것이 필요하다. 다중시기 영상에 대한 정규화 방법은 절대복사보정과 상대복사 보정으로 나눌 수 있으며, 본 연구에서는 상대복사 보정을 통한 시계열 위성영상처리 기법을 다루고자 한다. 2011년 3월 해일 피해가 발생했던 일본 센다이 지역을 연구대상지로 선정하였고, KOMPSAT-2 다중분광영상을 이용한 사고 전, 후의 피해지역 탐지에 있어 상대복사 보정의 실효성을 분석하였다. 다양한 상대복사 보정 기법 중에서 정준상관분석을 통해 PIFs(Pseudo Invariant Features) 지역을 자동으로 추출하는 MAD(Multivariate Alteration Detection) 기법을 적용하였다. 본 사례연구 분석결과 MAD 방식에 의한 자동 PIFs 지역의 추출은 비교적 높은 정확도 수준에서 이루어짐을 확인할 수 있었으며, 상대복사 보정된 시계열 위성영상을 사용함으로써 변화지역 자동탐지의 신뢰수준을 높일 수 있는 것으로 나타났다.

• 대한원격탐사학회지
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• 제23권3호
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• pp.153-160
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• 2007

Forest cover density studies using high resolution satellite data and object oriented classification are limited in India. This article focuses on the potential use of QuickBird satellite data and object oriented classification in forest density mapping. In this study, the high-resolution satellite data was classified based on NDVI/pixel based and object oriented classification methods and results were compared. The QuickBird satellite data was found to be suitable in forest density mapping. Object oriented classification was superior than the NDVI/pixel based classification. The Object oriented classification method classified all the density classes of forest (dense, open, degraded and bare soil) with higher producer and user accuracies and with more kappa statistics value compared to pixel based method. The overall classification accuracy and Kappa statistics values of the object oriented classification were 83.33% and 0.77 respectively, which were higher than the pixel based classification (68%, 0.56 respectively). According to the Z statistics, the results of these two classifications were significantly different at 95% confidence level.

• 한국농공학회논문집
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• 제53권3호
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• pp.75-82
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• 2011

This study refers to the derivation of simple crop yield prediction equation by using KOMPSAT-2 derived vegetation index. For a 1.25 ha small farm area located in the middle part of South Korea, the KOMPSAT-2 panchromatic and multi-spectral images of 31th August 2008, 17th November 2008, and 10th September 2009 were used. The field spectral reflectance during growing period for the 6 crops (rice, potato, corn, red pepper, garlic, and bean) were measured using ground spectroradiometer and the yield was investigated. Among the 6 vegetation indices (VI), the NDVI and ARVI between measured and image derived showed high relationship with the coefficient of determination of 0.85 and 0.95 respectively. Using the 3 years field data, the NDVI and ARVI regression curves were derived, and the yields were tried to compare with the maximum VIs value.