• 제목/요약/키워드: SPOT-5 Image

검색결과 142건 처리시간 0.019초

Development of New Photogrammetric Software for High Quality Geo-Products and Its Performance Assessment

  • Jeong, Jae-Hoon;Lee, Tae-Yoon;Rhee, Soo-Ahm;Kim, Hyeon;Kim, Tae-Jung
    • Korean Journal of Remote Sensing
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    • 제28권3호
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    • pp.319-327
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    • 2012
  • In this paper, we introduce a newly developed photogrammetric software for automatic generation of high quality geo-products and its performance assessment carried out using various satellite images. Our newly developed software provides the latest techniques of an optimized sensor modelling, ortho-image generation and automated Digital Elevation Model (DEM) generation for diverse remote sensing images. In particular, images from dual- and multi-sensor images can be integrated for 3D mapping. This can be a novel innovation toward a wider applicability of remote sensing data, since 3D mapping has been limited within only single-sensor so far. We used Kompsat-2, Ikonos, QuickBird, Spot-5 high resolution satellite images to test an accuracy of 3D points and ortho-image generated by the software. Outputs were assessed by comparing reliable reference data. From various sensor combinations 3D mapping were implemented and their accuracy was evaluated using independent check points. Model accuracy of 1~2 pixels or better was achieved regardless of sensor combination type. The high resolution ortho-image results are consistent with the reference map on a scale of 1:5,000 after being rectified by the software and an accuracy of 1~2 pixels could be achieved through quantitative assessment. The developed software offers efficient critical geo-processing modules of various remote sensing images and it is expected that the software can be widely used to meet the demand on the high-quality geo products.

A Proteomic Approach for Quantitative Analysis of Calcitonin Gene-related Peptides in the Cerebrospinal Fluid Obtained from a Rat Model of Chronic Neuropathic Pain (만성 신경병성 통증이 유발된 쥐의 뇌척수액에서 단백체학을 이용한 Calcitonin Gene-related Peptides의 정량분석)

  • Kim, Dong Hee;Hong, Sung Ho
    • The Korean Journal of Pain
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    • 제21권2호
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    • pp.112-118
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    • 2008
  • Background: This study was conducted to quantitatively analyze proteins associated with the calcitonin gene-related peptide (CGRP) in cerebrospinal fluid (CSF) that was obtained from a rat model of chronic neuropathic pain following administration of intrathecal $CGRP_{8-37}$. Methods: Male Sprague-Dawley rats (100-150 g, 5-6 wks) were divided into two groups, sham controls and neuropathic pain models. At the time of operation for neuropathic pain model, an intrathecal catheter was threaded through the intrathecal space. At 1 or 2 wks after the operation (maximum pain state), a test dose of 1, 5, 10, or 50 nM of $CGRP_{8-37}$ was injected into the intrathecal catheter and the CSF was then aspirated. Conventional proteomics to evaluate the CSF were then performed using high resolution 2-D, gel electrophoresis followed by computational image analysis and protein identification by mass spectrometry. Results: Treatment with $CGRP_{8-37}$ effectively alleviated mechanical allodynia in a dose dependent manner. The most effective response was obtained when a dose of 50 nM was administered, but significant differences were obtained following administration of only 5 nM $CGRP_{8-37}$. Furthermore, the results of the proteomic analysis were consistent with the experimental results. Specially we detected 30 differentially expressed spots in 7 images when 2-D gel electrophoresis was conducted. The intensity of 6 of these spots (spot number: 20 and 26-30) was found decrease the $CGRP_{8-37}$ dose increased; therefore, these spots were evaluated by mass spectrometry. This analysis identified 2 different proteins, CGRP (spot numbers: 26-30) and neurotensin-related peptide (spot number: 20). Conclusions: The results of this study suggest that CGRP plays a role in chronic central neuropathic pain and is a major target of chronic neuropathic pain management.

Research of 3D image processing of VR technology in medicine based on DNN

  • ZhaoZhe, Gong;XiaoDong, Li;XiaoYing, Shi;Geng, Liu;Bin, Chen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제16권5호
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    • pp.1584-1596
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    • 2022
  • According to a survey published in an authoritative journal in January 2020, the globalincidence rate of mental illness is 8.3% for men and 10.6% for women, which indicates thatmental illness has become a globally recognized obstacle. Therefore, specific psychotherapy including mental illness will become an important research topic. It is very effective forpatients with special mental diseases, such as mental illness, to reduce their mental reaction byexposure therapy; the system uses the virtual reality system of medical images processed by learningalgorithm to reproduce the effect of virtual reality exposure method of the high scene of transparent ladder. Compared with the old invasive exposure scene, the results show that theimprovement of both conditions has obvious effect, and the effect of human treatment underthe two conditions is not good. There are obvious differences, which show that virtual reality model will gradually replace the on-the-spot feeling. Finally, with more and more researchers have put forward a variety of other virtual reality image processing models, the research of image processing has gradually become more and more interested.

Analysis of Relation of Class Separability According to Different Kind of Satellite Images (위성영상의 종류에 따른 분리도 특성의 상관관계 분석)

  • Hong, Soon-Heon
    • The Journal of the Korea Contents Association
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    • 제7권1호
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    • pp.215-224
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    • 2007
  • The classification of the satellite images is basic part in Remote sensing. In classification of the satellite images, class separability feature is very effective accuracy of the images classified. For improving classification accuracy, It is necessary to study classification methode than analysis of class separability feature deciding classification probability. In this study, IKONOS, SPOT 5, Landsat TM, were resampled to sizes 1m grid. Above images were calculated the class separability prior to the step for classification of pixels. This Study concludes, each image was measured by the rate of class separability, values classified were showed highly about $1,600{\sim}2,000$.

Extraction of Bridge Status Using Satellite Image Data (인공위성 화상데이터를 이용한 교량위치의 추출)

  • 안기원;조병진;서두천
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • 제18권1호
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    • pp.33-40
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    • 2000
  • The aim of this study is to extract bridge location(center line and width of a bridge) from SPOT XS data with 20. The boundary pixels were computed to get the mixture proportions of classes and this mixture proportions were used to extract center line and width of a bridge. The accuracy was tested by comparing the extracted bridge center line coordinate and width to the existing 1:5,000 scale national digital map and field survey data. The results of the comparison show that the measuring accuracy of the bridge center line coordinates and width are $\pm$2.9 m and $\pm$4.1 m.

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Aberration Extraction Algorithm for LCD Defect Detection (대면적 LCD 결함검출을 위한 수차량 추출 알고리즘)

  • Ko, Jung-Hwan;Lee, Jung-Suk;Won, Young-Jin
    • 전자공학회논문지 IE
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    • 제48권4호
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    • pp.1-6
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    • 2011
  • In this paper we show the LCD simulator for defect inspection using image processing algorithm and neural network. The defect inspection algorithm of the LCD consists of preprocessing, feature extraction and defect classification. Preprocess removes noise from LCD image, using morphology operator and neural network is used for the defect classification. Sample images with scratch, pinhole, and spot from real LCD color filter image are used. From some experiments results, the proposed algorithms show that defect detected and classified in the ratio of 92.3% and 94.5 respectively. Accordingly, in this paper, a possibility of practical implementation of the LCD defect inspection system is finally suggested.

LCD Defect Detection using Neural-network based on BEP (BEP기반의 신경회로망을 이용한 LCD 패널 결함 검출)

  • Ko, Jung-Hwan
    • 전자공학회논문지 IE
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    • 제48권2호
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    • pp.26-31
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    • 2011
  • In this paper we show the LCD simulator for defect inspection using image processing algorithm and neural network. The defect inspection algorithm of the LCD consists of preprocessing, feature extraction and defect classification. Preprocess removes noise from LCD image, using morphology operator and neural network is used for the defect classification. Sample images with scratch, pinhole, and spot from real LCD color filter image are used. From some experiments results, the proposed algorithms show that defect detected and classified in the ratio of 92.3% and 94.5 respectively. Accordingly, in this paper, a possibility of practical implementation of the LCD defect inspection system is finally suggested.

Camera Modelling of Linear Pushbroom Images - Quality analysis of various algorithms (대표적 위성영상 카메라 모델링 알고리즘들의 비교연구)

  • 김태정;김승범;신동석
    • Korean Journal of Remote Sensing
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    • 제16권1호
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    • pp.73-86
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    • 2000
  • Commonly-used methods for camera modelling of pushbroom images were implemented and their performances were assessed. The models include Vector Propagation) model, Gugan and Downman(GD)'s model, Orun and Natarajan(ON)'s model, and Direct Linear Transformation(DLT) model The models were tested on a SPOT full-scene over Seoul. The number of ground control points(GCP) used range from 1 to 23. For less than 6 GCPs all other models fail except VP, with VP's accuracy being 2.7 pixels. With mode than 6 GCPs ON shows the best accuracy with 1pixel accuracy while the accuracy of VP is 1.5 pixels. GD fails in most cases due to the correlation among model parameters. The accuracy of DLT does not converge but fluctuates between 1 and 4 pixels subject to GCPs used. VP has an advantage in that its results can be used for the estimation of satellite orbit. Unresolved topics are: to remove errors in GCPs from the aforementioned accuracy value; to improve the performance of VP.

EUVL Mask Defect Isolation and Repair using Focused Ion Beam (Focused Ion Beam을 이용한 EUVL Mask Defect Isolation 및 Repair)

  • 김석구;백운규;박재근
    • Journal of the Semiconductor & Display Technology
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    • 제3권2호
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    • pp.5-9
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    • 2004
  • Microcircuit fabrication requires precise control of impurities in tiny regions of the silicon. These regions must be interconnected to create components and VLSI circuits. The patterns to define such regions are created by lithographic processes. In order to image features smaller than 70 nm, it is necessary to employ non-optical technology (or next generation lithography: NGL). One such NGL is extreme ultra-violet lithography (EUVL). EUVL transmits the pattern on the wafer surface after reflecting ultra-violet through mask pattern. If particles exist on the blank mask, it can't transmit the accurate pattern on the wafer and decrease the reflectivity. It is important to care the blank mask. We removed the particles on the wafer using focused ion beam (FIB). During removal, FIB beam caused damage the multi layer mask and it decreased the reflectivity. The relationship between particle removal and reflectivity is examined: i) transmission electron microscope (TEM) observation after particle removal, ii) reflectivity simulation. It is found that the image mode of FIB is more effective for particle removal than spot and bar mode.

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Algorithm and Performance Evaluation of High-speed Distinction for Condition Recognition of Defective Nut (불량 너트의 상태인식을 위한 고속 판별 알고리즘 및 성능평가)

  • Park, Tae-Jin;Lee, Un-Seon;Lee, Sang-Hee;Park, Man-Gon
    • Journal of Korea Multimedia Society
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    • 제14권7호
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    • pp.895-904
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    • 2011
  • In welding machine that executes existing spot welding, wrong operation of system has often occurs because of their mechanical motion that can be caused by a number of supply like the welding object. In exposed working environment for various situations such as worker or related equipment moving into any place that we are unable to exactly distinguish between good and not condition of nut. Also, in case of defective welding of nut, it needs various evaluation and analysis through image processing because the problem that worker should be inspected every single manually. Therefore in this paper, if the object was not stabilization state correctly, we have purpose to algorithm implementation that it is to reduce the analysis time and exact recognition as to improve system of image processing. As this like, as image analysis for assessment whether it is good or not condition of nut, in his paper, implemented algorithms were suggested and list by group and that it showed the effectiveness through more than one experiment. As the result, recognition rate of normality and error according to the estimation time have been shown as 40%~94.6% and 60%~5.4% from classification 1 of group 1 to classification 11 of group 5, and that estimation time of minimum, maximum, and average have been shown as 1.7sec.~0.08sec., 3.6sec.~1.2sec., and 2.5sec.~0.1sec.