• Title/Summary/Keyword: multi-spectral images

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MSC(Multi-Spectral Camera) 열제어 시스템 소개

  • Kong, Jong-Pil;Heo, Haeng-Pal;Kim, Young-Sun;Park, Jong-Euk;Jang, Young-Jun
    • Aerospace Engineering and Technology
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    • v.4 no.2
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    • pp.107-116
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    • 2005
  • As a unique payload of Komsat-2, MSC, comprising EOS(Electro-Optical Sub-system), PMU(Payload Management Unit) and PDTS(Payload Data Transmission Sub-system), is supposed to take pictures of one panchromatic and 4 multi-spectral image between wavelength 450mm~900mm, and is being under final Satellite I&T. It will perform the earth remote sensing with applications such as acquisition of high resolution images, surveillance of large scale disasters and its countermeasure, survey of natural resources, etc.. Under the hostile influence of the extreme space environmental conditions due to deep space and direct solar flux, the thermal design is especially of major importance in designing a payload. There are tight temperature range restrictions for electro-optical elements while on the other hand there are low power consumption requirements due to the limited energy source on the spacecraft. This paper describes details of thermal control system for MSC.

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Photogrammetry 기법을 활용한 MSC 설치면의 정밀 측정

  • Woo, Sung-Hyun;Kim, Hong-Bae;Moon, Sang-Mu;Im, Jong-Min
    • Aerospace Engineering and Technology
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    • v.3 no.1
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    • pp.126-133
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    • 2004
  • Photogrammetry, as its name implies, is a 3-dimensional coordinate measuring technique that uses photographs as the fundamental medium for metrology. In the last few years the accuracy of photogrammetry has increased dramatically thanks to the rapid advance of digital camera manufacturing technique. This paper discusses photogrammetric measurement of the interface surface of MSC(Multi-Spectral Camera), which is a main payload of KOMPSAT-2. Total 24 paper targets on the objective surfaces and two scale bars calibrated with high accuracy were used for measurement, and multiple images were taken from 11 different camera angles by using a spacecraft rotation dolly. As a result of analysis, 3D coordinates of each targeted point were obtained and the flatness value based on the selected reference plane was calculated and compared with the pre-determined requirement. The technique acquired by this study is expected to be used for the 3D precise measurement of ultra-light weight and inflatable space structures such as a satellite antenna and a solar array.

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Pattern Classification of Multi-Spectral Satellite Images based on Fusion of Fuzzy Algorithms (퍼지 알고리즘의 융합에 의한 다중분광 영상의 패턴분류)

  • Jeon, Young-Joon;Kim, Jin-Il
    • Journal of KIISE:Software and Applications
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    • v.32 no.7
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    • pp.674-682
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    • 2005
  • This paper proposes classification of multi-spectral satellite image based on fusion of fuzzy G-K (Gustafson-Kessel) algorithm and PCM algorithm. The suggested algorithm establishes the initial cluster centers by selecting training data from each category, and then executes the fuzzy G-K algorithm. PCM algorithm perform using classification result of the fuzzy G-K algorithm. The classification categories are allocated to the corresponding category when the results of classification by fuzzy G-K algorithm and PCM algorithm belong to the same category. If the classification result of two algorithms belongs to the different category, the pixels are allocated by Bayesian maximum likelihood algorithm. Bayesian maximum likelihood algorithm uses the data from the interior of the average intracluster distance. The information of the pixels within the average intracluster distance has a positive normal distribution. It improves classification result by giving a positive effect in Bayesian maximum likelihood algorithm. The proposed method is applied to IKONOS and Landsat TM remote sensing satellite image for the test. As a result, the overall accuracy showed a better outcome than individual Fuzzy G-K algorithm and PCM algorithm or the conventional maximum likelihood classification algorithm.

Band Selection Using Forward Feature Selection Algorithm for Citrus Huanglongbing Disease Detection

  • Katti, Anurag R.;Lee, W.S.;Ehsani, R.;Yang, C.
    • Journal of Biosystems Engineering
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    • v.40 no.4
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    • pp.417-427
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    • 2015
  • Purpose: This study investigated different band selection methods to classify spectrally similar data - obtained from aerial images of healthy citrus canopies and citrus greening disease (Huanglongbing or HLB) infected canopies - using small differences without unmixing endmember components and therefore without the need for an endmember library. However, large number of hyperspectral bands has high redundancy which had to be reduced through band selection. The objective, therefore, was to first select the best set of bands and then detect citrus Huanglongbing infected canopies using these bands in aerial hyperspectral images. Methods: The forward feature selection algorithm (FFSA) was chosen for band selection. The selected bands were used for identifying HLB infected pixels using various classifiers such as K nearest neighbor (KNN), support vector machine (SVM), naïve Bayesian classifier (NBC), and generalized local discriminant bases (LDB). All bands were also utilized to compare results. Results: It was determined that a few well-chosen bands yielded much better results than when all bands were chosen, and brought the classification results on par with standard hyperspectral classification techniques such as spectral angle mapper (SAM) and mixture tuned matched filtering (MTMF). Median detection accuracies ranged from 66-80%, which showed great potential toward rapid detection of the disease. Conclusions: Among the methods investigated, a support vector machine classifier combined with the forward feature selection algorithm yielded the best results.

QUICK-LOOK TEST OF KOMPSAT-2 FOR IMAGE CHAIN VERIFICATION

  • Lee Eung-Shik;Jung Dae-Jun;Lee Seung-Hoon
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.509-511
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    • 2005
  • KOMPSAT -2 equipped with an optical telescope(MSC) will be launched in this year. It can take images of the earth with push-broom scanning at altitude 685Km. Its resolution is 1m in panchromatic channel with a swath width of 15 km After the MSC is tested and the performance is measured at instrument level, it is installed on satellite. The image passes through the electro-optical system, compression and storage unit and fmally downlink sub-systems. This integration procedure necessitates the functional test of all subsystems participating in the image chain. The objective of functional test at satellite level(Quick Look test) is to check the functionality of image chain by real target image. Collimated moving image is input to the EOS in order to simulate the operational environments as if KOMPSAT -2 is being operated in orbit. The image chain from EOS to data downlink subsystem will be verified through Quick Look test. This paper explains the Quick Look test of KOMPSAT -2 and compares the taken images with collimated input ones.

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Monitoring algal bloom in river using unmanned aerial vehicle(UAV) imagery technique (UAV(Unmanned aerial vehicle)를 활용한 하천 녹조 모니터링 평가)

  • Kim, Eun-Ju;Nam, Sook-Hyun;Koo, Jae-Wuk;Hwang, Tae-Mun
    • Journal of Korean Society of Water and Wastewater
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    • v.32 no.6
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    • pp.573-581
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    • 2018
  • The purpose of this study is to evaluate the fixed wing type domestic UAV for monitoring of algae bloom in aquatic environment. The UAV used in this study is operated automatically in-flight using an automatic navigation device, and flies along a path targeting preconfigured GPS coordinates of desired measurement sites input by a flight path controller. The sensors used in this study were Sequoia multi-spectral cameras. The photographed images were processed using orthomosaics, georeferenced digital surface models, and 3D mapping software such as Pix4D. In this study, NDVI(Normalized distribution vegetation index) was used for estimating the concentration of chlorophyll-a in river. Based on the NDVI analysis, the distribution areas of chlorophyll-a could be analyzed. The UAV image was compared with a airborne image at a similar time and place. UAV images were found to be effective for monitoring of chlorophyll-a in river.

Investigating the cosmic evolution of the black hole mass-bulge luminosity scaling relation

  • Park, Daeseong;Woo, Jong-Hak;Treu, Tommaso;Bennert, Vardha N.;Malkan, Matthew A.;Auger, Matthew W.
    • The Bulletin of The Korean Astronomical Society
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    • v.38 no.2
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    • pp.42.2-42.2
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    • 2013
  • We investigate the cosmic evolution of the black hole mass-bulge luminosity relation with a sample of 52 moderate-luminosity AGNs at $z{\simeq}0.36$ and $z{\simeq}0.57$, corresponding to look-back times of 4 and 6 Gyrs. By employing robust multi-component spectral and structural decomposition methods to the obtained high-quality Keck spectra and high-resolution HST images, black hole masses ($M_{BH}$) are estimated from the Hbeta broad emission line with the 5100A nuclear luminosity, and bulge luminosities ($L_{bul}$) are derived from the surface photometry. Based on these consistent measurements, we constrain the redshift evolution of the $M_{BH}-L_{bul}$ relation by performing the Monte Carlo simulations designed to account for selection effects. We provide implications of our results in terms of the black hole-galaxy co-evolution and discuss possible bulge growth mechanisms.

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AUTOMATIC IMAGE SEGMENTATION OF HIGH RESOLUTION REMOTE SENSING DATA BY COMBINING REGION AND EDGE INFORMATION

  • Byun, Young-Gi;Kim, Yong-II
    • Proceedings of the KSRS Conference
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    • 2008.10a
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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.

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HOST GALAXY OF TIDAL DISRUPTION OBJECT, SWIFT J1644+57

  • YOON, YONGMIN;IM, MYUNGSHIN;LEE, SEONG-KOOK;PAK, SOOJONG
    • Publications of The Korean Astronomical Society
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    • v.30 no.2
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    • pp.475-476
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    • 2015
  • We analyze the host galaxy of the tidal disruption object, Swift J1644+57, based on long-term optical to NIR data obtained with CQUEAN and UKIRT WFCAM observations. We decompose the bulge component using high resolution HST WFC3 images. We conclude that the host galaxy is bulge dominant. We investigate optical to NIR light curves and estimate the multi-band fluxes of the host galaxy. We fit spectral energy distribution (SED) models in order to determine the stellar mass. Finally, we estimate the mass of the black hole in the center of the host galaxy based on several scale relations.

Development of KITSAT-3 camera and current status of the operation (우리별 3호 지구관측 카메라 개발 및 운용 현황)

  • 이준호;유상근
    • Korean Journal of Optics and Photonics
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    • v.12 no.5
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    • pp.382-388
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    • 2001
  • KITSAT-3, launched at May 26 1999, has an earth observation optical payload named MEIS (Multi-spectral Earth Imaging System). The MEIS is a Managin mirror telescope of aperture size of 95mm, and it images the ground with the ground sampling distance of 13.8m over 48km at the altitude of 720km using three different observations bands. This paper first presents the design and then the optics, relating results of manufacturing, integration and test. Finally it briefly discusses the current status of MEIS operation.

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