• 제목/요약/키워드: Advanced Fusion Technology

검색결과 558건 처리시간 0.029초

LANDSAT-5 TM 영상의 대기보정에 따른 클래스별 화소값 분포 변화 비교 (Comparison of Digital Number Distribution Changes of Each Class according to Atmospheric Correction in LANDSAT-5 TM)

  • 정태웅;어양담;김태렬;임상범;박두열;박황수;박명학;박완용
    • 대한원격탐사학회지
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    • 제25권1호
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    • pp.11-20
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    • 2009
  • 우리나라는 황사발생 빈도가 증가하고 특히 하절기에 강우 및 구름 발생이 잦아 위성원격탐사영상의 대기보정처리를 필요로 한다. 본 연구에서는 대기보정 전후의 클래스별 화소값 분포 변화를 비교하여 대기보정이 영상화소분류에 미치는 영향을 분석하였다. 실험에 사용된 영상은 LANDSAT-5 TM이고, 대기보정 모듈로는 상용 소프트웨어인 ATCOR, FLAASH와 인터넷에 공개된 COST 모델 3가지를 적용하였다. 실험 결과, 건물밀집 지역 영역에서 클래스 분리도가 향상되는 것으로 나타났다.

지능 로봇 시스템을 위한 다중 센서 데이타 Fusion (Multisensor Data Fusion for Intelligent Robot Systems)

  • 김완주;고중협;정명진
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1991년도 하계학술대회 논문집
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    • pp.787-794
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    • 1991
  • The objective of this paper is to survey the state of the art of multisensor data fusion in intelligent robot systems. The variety of approaches to the problem of multisensor fusion ranging from general frameworks to robotic applications is surveyed. We have classified them into three categories : sensor modeling, fusional methods, and robotic applications. Also we present research trend and future direction of multisensor fusion.

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Effectiveness of Using the TIR Band in Landsat 8 Image Classification

  • Lee, Mi Hee;Lee, Soo Bong;Kim, Yongmin;Sa, Jiwon;Eo, Yang Dam
    • 한국측량학회지
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    • 제33권3호
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    • pp.203-209
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    • 2015
  • This paper discusses the effectiveness of using Landsat 8 TIR (Thermal Infrared) band images to improve the accuracy of landuse/landcover classification of urban areas. According to classification results for the study area using diverse band combinations, the classification accuracy using an image fusion process in which the TIR band is added to the visible and near infrared band was improved by 4.0%, compared to that using a band combination that does not consider the TIR band. For urban area landuse/landcover classification in particular, the producer’s accuracy and user’s accuracy values were improved by 10.2% and 3.8%, respectively. When MLC (Maximum Likelihood Classification), which is commonly applied to remote sensing images, was used, the TIR band images helped obtain a higher discriminant analysis in landuse/landcover classification.

FUSION MATERIALS AND FUSION ENGINEERING R&D IN JAPAN

  • KOHYAMA A.;KONISHI S.;KIMURA A.
    • Nuclear Engineering and Technology
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    • 제37권5호
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    • pp.423-432
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    • 2005
  • Japanese activities on fusion structural materials R&D have been well organized under the coordination of university programs and JAERI/NIMS programs more than two decades. Where, two categories of structural materials have been studied, those are; reduced activation martensitic/ferritic steels (RAFs) as reference material and vanadium alloys and SiC/SiC composite materials as advanced materials. The R&D histories of these candidate materials and the present status in Japan are reviewed with the emphasis on materials behavior under radiation damage. The importance of IFMIF and technology development for blanket R&D including ITER-TBRG activity is emphasized and the current status of those activities in Japan is also presented.

퍼지기법을 이용한 다중 센서 데이타 Fusion (Multisensor Data Fusion Using Fuzzy Techniques)

  • 김완주;고중협;정명진
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1991년도 하계학술대회 논문집
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    • pp.781-786
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    • 1991
  • This paper introduces a new methodology for multisensor data fusion. The method makes use of fuzzy techniques and possibility distribution as a fuzzy restriction which acts as an elastic constraint on the values that may be assigned to a variable. We propose a simple sensor fuzzy modeling method which can be used for cluster validity analysis. As a result, the feasibility of these multisensor data fusion modules is demonstrated by computer simulation applicable to the problem of object identification.

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Motion and Structure Estimation Using Fusion of Inertial and Vision Data for Helmet Tracker

  • Heo, Se-Jong;Shin, Ok-Shik;Park, Chan-Gook
    • International Journal of Aeronautical and Space Sciences
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    • 제11권1호
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    • pp.31-40
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    • 2010
  • For weapon cueing and Head-Mounted Display (HMD), it is essential to continuously estimate the motion of the helmet. The problem of estimating and predicting the position and orientation of the helmet is approached by fusing measurements from inertial sensors and stereo vision system. The sensor fusion approach in this paper is based on nonlinear filtering, especially expended Kalman filter(EKF). To reduce the computation time and improve the performance in vision processing, we separate the structure estimation and motion estimation. The structure estimation tracks the features which are the part of helmet model structure in the scene and the motion estimation filter estimates the position and orientation of the helmet. This algorithm is tested with using synthetic and real data. And the results show that the result of sensor fusion is successful.