• 제목/요약/키워드: SPOT image

검색결과 479건 처리시간 0.032초

A New Spatial Interpolation Method of GCP Datum of Remote Sensing Images

  • Ren, Liucheng
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.1365-1367
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    • 2003
  • A new method, called dynamic space projection method that is suitable to remote sensing image, is adopted to encrypt GCP (ground control point) datum in this paper. The essence of this method is to encrypt enough GCP by using a few known GCP in order to realize the precise correction of remote sensing image. By making use of the method to the GCP datum encrypting and precise geometric correction of TM image and SPOT image, the precision of encrypted GCP is less than one pixel, the precision of precisely corrected image is less than two pixels.

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칼라 및 질감 속성 벡터를 이용한 위성영상의 분류 (Satellite Image Classification Based on Color and Texture Feature Vectors)

  • 곽장호;김준철;이준환
    • 대한원격탐사학회지
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    • 제15권3호
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    • pp.183-194
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    • 1999
  • 위성에서 관측된 다중분광 위성영상 데이터를 이용목적에 따라 분석하고 활용하기 위해서는 영상 자체에 내포된 밝기, 칼라, 질감 등 다양한 특징들이 중요한 정보원으로 이용되고 있다. 특히 질감이나 칼라정보를 이용한 위성영상의 분석과정에서 가장 중요한 문제는 원 영상의 정보를 효율적으로 표현하는 속성을 추출하여 적절히 활용하는 것이다. 따라서 본 논문에서는 위성영상 분석에 유용하게 사용할 수 있는 6개의 속성 벡터들을 선정한 다음 SPOT 위성에서 관측된 영상을 이용하여 각각의 속성들에 대한 분별력을 평가하기 위하여 역전파 신경망(Back-propagation Neural Network)을 이용한 분류 네트워크를 구성하였고, 실험하고자 하는 지역에 대한 훈련집합 선택시 선정된 여섯 개이 속성 벡터들을 분류에 사용될 특징으로 선택하였다. 분류 실험을 수행한 결과 각각의 벡터 속성들은 개개의 특성에 따라 많은 장단을 내포하고 있었으며, 전반적으로는 비교적 정확한 분류결과를 나타내었다. 따라서 칼라 및 질감 속성 벡터들은 위성영상의 분류과정에 효과적으로 사용될 수 있음은 물론 다양한 영상분석 및 응용분야에서도 유용하게 이용될 수 있을 것으로 기대된다.

지역문화회관 로비공간의 이미지 형성요소와 평가에 관한 연구 (T A Study on the Composition Elements and Evaluation of Image in Lobby of the Local Cultural Institution)

  • 손광호;강혜경
    • 한국실내디자인학회논문집
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    • 제17권3호
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    • pp.68-76
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    • 2008
  • This study investigated composition elements and estimation of image in lobby from user viewpoint that is the central space of local cultural institution, and spectator mainly utilizes. Progress process of study develops investigation device including literature investigation, professional panel and lobby space image measurement tool through on-the-spot probe and, executed supporting research to spectator. As the result of the study, first, lobby space image exerts absolute effect to local cultural institution image-building, and is grasped on constituent that floor, ceiling, entrance and lighting and decoration is important in image-building of lobby space. Second, the image of the important lobby space was grasped in order of convenient image(M = 3.98) bright image(M = 3.87), and cozy image(M = 3.80). Third, the results on investigating semantic structure of the lobby image, emotional factor, styling factor, spatial factor, and peculiar factor are composed of important factors that decides image of lobby space. Fourth, as the result of image analysis for lobby space, the degree of satisfaction for the local cultural institution was entirely low against the importance. In particular, the image for convenience, individuality, locality and dignity was not sufficient in all the three places. Therefore, lobby design of local cultural institution shall also suggest more various lobby space image from culture oriented viewpoint.

위성영상을 이용한 토지피복 분류 및 SCS 유출량 산정 (Land Cover Classification and SCS Runoff Estimation using Remotely Sensed Imaged)

  • 이윤아;함종화;장석길;김성준
    • 한국농공학회:학술대회논문집
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    • 한국농공학회 1999년도 Proceedings of the 1999 Annual Conference The Korean Society of Agricutural Engineers
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    • pp.544-549
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    • 1999
  • The objective of this study is to identify the applicability of land cover image classified by remotely sensed data ; Landsat TM merged by SPOT for hydrological applications such as SCS runoff estimation . By comparing the calssified land cover image with the statistical data, it was proved that hey are agreed well with little errors. As a simple application , SCS runoff estimation was tested by varying rainfall intensity and AMC with Soilmap classfied by hydrologica soil map.

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Adaptive Parametric Estimation and Classification of Remotely Sensed Imagery Using a Pyramid Structure

  • Kim, Kyung-Sook
    • 대한원격탐사학회지
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    • 제7권1호
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    • pp.69-86
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    • 1991
  • An unsupervised region based image segmentation algorithm implemented with a pyramid structure has been developed. Rather than depending on thraditional local splitting and merging of regions with a similarity test of region statistics, the algorithm identifies the homogenous and boundary regions at each level of pyramid, then the global parameters of esch class are estimated and updated with values of the homogenous regions represented at the level of the pyramid using the mixture distribution estimation. The image is then classified through the pyramid structure. Classification results obtained for both simulated and SPOT imagery are presented.

MODELING SATELLITE IMAGE STRIPS WITH COLLINEARITY-BASED AND ORBIT-BASED SENSOR MODELS

  • Kim, Hyun-Suk;Kim, Tae-Jung
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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    • pp.578-581
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    • 2006
  • Usually to achieve precise geolocation of satellite images, we need to get GCPs (Ground control points) from individual scenes. This requirement greatly increases the cost and processing time for satellite mapping. In this article, we focus on finding appropriate sensor models for entire image strips composing of several adjacent scenes. We tested the feasibility of modelling whole satellite image strips by establishing sensor models of one scene with GCPs and by applying the models to neighboring scenes without GCPs. For this, we developed two types of sensor models: collinearity-based type and orbit-based type and tested them using different sets of unknowns. Results indicated that although the performance of two types was very similar, for modelling individual scenes, it was not for modelling the whole strips. Moreover, the performance of sensor models was remarkably sensitive to different sets of unknowns. It was found that the orbit-based model using attitude biases as unknowns can be used to model SPOT image strips of 420 Km in length.

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Multi- Resolution MSS Image Fusion

  • Ghassemian, Hassan;Amidian, Asghar
    • 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.

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양극의 경사각 효과에 따른 조사야 X-선 강도 분포 (Distribution of X-ray Strength in Exposure Field Caused by Heel Effect)

  • 장근조;김남훈;이준행;이상복
    • 한국방사선학회논문지
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    • 제5권5호
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    • pp.223-229
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    • 2011
  • X선은 X선관 내 음극측 전자(electron)를 빠른 속도로 가속시킨 다음 진행하는 전자의 흐름을 저지극(target)에서 차단시킬 때 에너지의 변환을 일으켜 발생한다. 가속된 고속의 전자가 저지면에 충돌하는 실제면적을 실초점(actual focal spot)이라 하고, 실초점의 크기를 X선이 나오는 방향인 중심선(central ray)측에서 관측할 경우 축소되어 작게 보이는데 이때의 초점을 실효초점(effective focal spot)이라고 한다. X선관 방사각에 따라 음극 측의 강도가 양극 측 보다 높게 나타나 X선 강도가 균등하지 않다. 이러한 효과를 경사각 효과(heel effect)라고 하며, 경사각 효과로 인하여 환자가 받는 피폭의 정도는 양극의 각도, 즉 실효초점의 크기에 따라 달라지게 된다. 본 논문에서는 실효초점의 크기와 그에 따른 환자 피폭선량의 상관관계를 알아보고 실효초점의 크기에 따른 균질선량 분포를 위한 효과적인 조사야를 제시하고자 한다. 결론적으로 초점크기에 따라서 평균적으로 -8cm ~ 0cm 범위에서 효과적인 조사야 범위를 찾을 수 있었고, 평균 선량률은 0.019 R/min이 나왔다. 이 범위를 이용하면 환자에게는 적은 피폭선량으로 균등한 흑화도 및 해상력을 가진 영상을 얻을 수 있을 것이다.

딥러닝 알고리즘을 이용한 인쇄된 별색 잉크의 색상 예측 연구 (A Study on A Deep Learning Algorithm to Predict Printed Spot Colors)

  • 전수현;박재상;태현철
    • 산업경영시스템학회지
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    • 제45권2호
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    • pp.48-55
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    • 2022
  • The color image of the brand comes first and is an important visual element that leads consumers to the consumption of the product. To express more effectively what the brand wants to convey through design, the printing market is striving to print accurate colors that match the intention. In 'offset printing' mainly used in printing, colors are often printed in CMYK (Cyan, Magenta, Yellow, Key) colors. However, it is possible to print more accurate colors by making ink of the desired color instead of dotting CMYK colors. The resulting ink is called 'spot color' ink. Spot color ink is manufactured by repeating the process of mixing the existing inks. In this repetition of trial and error, the manufacturing cost of ink increases, resulting in economic loss, and environmental pollution is caused by wasted inks. In this study, a deep learning algorithm to predict printed spot colors was designed to solve this problem. The algorithm uses a single DNN (Deep Neural Network) model to predict printed spot colors based on the information of the paper and the proportions of inks to mix. More than 8,000 spot color ink data were used for learning, and all color was quantified by dividing the visible light wavelength range into 31 sections and the reflectance for each section. The proposed algorithm predicted more than 80% of spot color inks as very similar colors. The average value of the calculated difference between the actual color and the predicted color through 'Delta E' provided by CIE is 5.29. It is known that when Delta E is less than 10, it is difficult to distinguish the difference in printed color with the naked eye. The algorithm of this study has a more accurate prediction ability than previous studies, and it can be added flexibly even when new inks are added. This can be usefully used in real industrial sites, and it will reduce the attempts of the operator by checking the color of ink in a virtual environment. This will reduce the manufacturing cost of spot color inks and lead to improved working conditions for workers. In addition, it is expected to contribute to solving the environmental pollution problem by reducing unnecessarily wasted ink.

인공위성 원격탐사의 활용: 김양식장의 현황 모니터링 (Satellite Remote Sensing Application: Facilities Analysis of Laver Cultivation Grounds System)

  • 양찬수;문정언;이누리;박성우
    • 해양환경안전학회:학술대회논문집
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    • 해양환경안전학회 2006년도 춘계학술발표회
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    • pp.47-52
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    • 2006
  • 연안 김 양식장의 효과적 관리를 위해서는 실제 시설량의 조사가 필요하며, 인공위성을 이용한 방법이 가장 효과적이다. 본 연구에서는 10m의 해상도를 갖고 있는 SPOT-5 다중분광영상을 사용하였으며, 김 양식장의 자동탐지알고리듬의 개발을 위하여 경기도 화성시 제부도 남방해역에 대한 2005년도 영상을 사용하였다. 김 양식장을 추출하기 위하여 우선 3밴드 영상의 분광특성을 이용한 밴드차(Band difference) 영상을 작성하여, 두 가지 방법 (형태학적 처리기법 및 Canny 에지 탐지기법)으로 처리를 한 후, 두 결과를 합성하여 라벨링함으로써 탐지율을 극대화하였다. 마지막으로 2005년 우리나라 연안의 김 양식장에 대한 인공위성 조사 결과, 실제 시설량은 676,749 책(柵)으로, 면허시설량 572,745 책보다 다소 많은 것으로 나타났다. 양식장 시설 현황 조사 결과는, 정부에서 전체 생산량을 조절할 수 있게 하며, 양식업자가 좋은 수확을 달성하는데 도움이 될 수 있을 것이다.

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