• Korean Journal of Environment and Ecology
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• v.9 no.2
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• pp.232-249
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• 1996

The purpose of this is to suggest objective basic data for the use development and conservation management of the national park through the quantitative analysis of the visual quality included in the physical environment of the Odaesan National Park, for this, spatial images structure of physical elements have been analyzed by factor analysis algorithm and degree of visual quality have been measured mainly by questionnaries. Result of this thesis can be summarized as follows. Factors covering the spatial image of the Odaesan National Park landscape have been found to be the pverall synthetic evaluation, physical, spatial, natural quality and, appeal factors such as the overall the synthetic evaluation, spatial and appeal yield high factor scores. As for the factors determining the degree of visual quality of clear of valley, peculiarity of configuration, natural of trail, harmony of suitable artificaial planting and temple.

• Computers and Concrete
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• v.21 no.6
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• pp.727-739
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• 2018

Crack is the most common typical feature of concrete deterioration, so routine monitoring and health assessment become essential for identifying failures and to set up an appropriate rehabilitation strategy in order to extend the service life of concrete structures. At present, image segmentation algorithms have been applied to crack analysis based on inspection images of concrete structures. The results of crack segmentation offering crack information, including length, width, and area is helpful to assist inspectors in surface inspection of concrete structures. This study proposed an algorithm of image segmentation enhancement, named morphological segmentation based on edge detection-II (MSED-II), to concrete crack segmentation. Several concrete pavement and building surfaces were imaged as the study materials. In addition, morphological operations followed by cross-curvature evaluation (CCE), an image segmentation technique of linear patterns, were also tested to evaluate their performance in concrete crack segmentation. The result indicates that MSED-II compared to CCE can lead to better quality of concrete crack segmentation. The least area, length, and width measurement errors of the concrete cracks are 5.68%, 0.23%, and 0.00%, respectively, that proves MSED-II effective for automatic measurement of concrete cracks.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.305-308
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• 2002

More complex radiotherapy techniques using multi leaf collimation(MLC) such as intensity-modulated radiation therapy(IMRT) has been increasing the significance of verification of leaf position and motion. Due to the reliability and robustness, quality assurance(QA) of MLC is usually performed with portal films. However, the advantage of ease of use and capability of providing digital data of electronic portal imaging devices(EPIDs) have attracted many attentions as alternatives of films for routine quality assurance in spite of the concerns about their clinical feasibility, efficacy, and the cost to benefit ratio. In our work, the method of routine QA of MLC using electronic portal imaging(EPI) was developed. The verification of availability of EPI images for routine QA was performed by comparison with those of the portal films which were simultaneously obtained when radiation was delivered and known prescription input to MLC controller. Specially designed test patterns of dynamic MLC were applied to image acquisition. Quantitative off-line analysis using edge detection algorithm enhanced the verification procedure in addition to on-line qualitative visual assessment. In conclusion, the EPI is available enough for routine QA with the accuracy of portal films.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.4
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• pp.463-469
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• 2010

Since MOLA(Mars Orbiter Laser Altimeter) data, which provides altimetry data for Mars, does not cover the whole Mars area, image matching with MOC imagery should be implemented for the generation of DEM. However, automatic image matching is difficult because of insufficient features and low contrast. In this paper, we present the area based semi-automatic image matching algorithm with MOC-NA(Mars Orbiter Camera ? Narrow Angle) imagery. To accomplish this, seed points describing conjugate points are manually added for the stereo imagery, and interesting points are automatically produced by using such seed points. Produced interesting points being used as initial conjugate points, area based image matching is implemented. For the points which fail to match, the locations of initial conjugate points are recalculated by using matched six points and image matching process is re-implemented. The quality assessment by reversing the role of target and search image shows 97.5 % of points were laid within one pixel absolute difference.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.4
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• pp.359-365
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• 2008

This paper focused on generation of more accurate DEM and analysis of accuracy. For this, we applied suitable sensor modeling technique for each satellite image and automatic pyramid matching using image pyramid was applied. Matching algorithm based on epipolarity and scene geometry also was applied for stereo matching. IKONOS, Quickbird, SPOT-5, Kompsat-2 were used for experiments. In particular, we applied orbit-attitude sensor modeling technique for Kompsat-2 and performed DEM generation successfully. All DEM generated show good quality. Assessment was carried out using USGS DTED and we also compared between DEM generated in this research and DEM generated from common software. All DEM had $9m{\sim}12m$ Mean Absolute Error and $13m{\sim}16m$ RMS Error. Experimental results show that the DEMs of good performance which is similar to or better than result of DEMs generated from common software.

• Journal of Korean Society of Forest Science
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• v.85 no.2
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• pp.195-209
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• 1996

The purpose of this study is to suggest objective basic data for the national park development through the quantitative analysis of the visual quality included in the physical environment of the Dukyu National Park. For this, spatial images structure of physical elements have been analyzed by factor analysis algorithm and degree of visual quality have been measured mainly by questionnaires. Result of this thesis can be summarized as follows. Factors covering the spatial image of the Dukyu National Park landscape have been found to be the overall synthetic evaluation spatial, appeal, natural quality and physical factors such as the overall the synthetic evaluation, spatial and appear yield high factor scores. Thus, these factors can be considered to represent the site spatial image of Dukyu Korean-National Park. By using the control method for the number of factors, Total variance explained by the factors has been obtained as 45.46% and 45.45%. Principal variables of main factors explained above may be the scaling containing the functional criteria of quantitative approach for landscape management of national park development. According to difference of special image from each place, for these variables that decided the visual quality can be differed, and even the same place due to landscape control point change the visual quality can be affected affirmately or negatively, according to recognized by the landscape control point.

• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.861-871
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• 2019

Landsat satellite images have been increasingly used for disaster damage analysis and disaster monitoring because they can be used for periodic and broad observation of disaster damage area. However, periodic disaster monitoring has limitation because of areas having missing data due to clouds as a characteristic of optical satellite images. Therefore, a study needs to be conducted for restoration of missing areas. This study detected and removed clouds and cloud shadows by using the quality assessment (QA) band provided when acquiring Landsat-8 images, and performed image restoration of removed areas through a spatial and temporal adaptive reflectance fusion (STARFM) algorithm. The restored image by the proposed method is compared with the restored image by conventional image restoration method throught MLC method. As a results, the restoration method by STARFM showed an overall accuracy of 89.40%, and it is confirmed that the restoration method is more efficient than the conventional image restoration method. Therefore, the results of this study are expected to increase the utilization of disaster analysis using Landsat satellite images.

• Journal of the Korean Society of Radiology
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• v.8 no.4
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• pp.147-153
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• 2014

We tried to assessment about characteristics of image through quantitative evaluation method and qualitative evaluation method in Full Field Digital Mammography. It satisfied an approval standard of ten score regardless of compression ratio measuring detection score after compressing and appling an algorithm of JPEG2000 orJPEG compression targeting ACR accreditation phantom. Also, it was apparent that when we selected and compressed the image of real fine lesion and measured a change of diagnosis ability magnifing over 50 percent after compressing over 20:1 ratio, it had a strong influence on diagnosis ability. We realized that the difference between the original image according to compression ratio measuring a quantitative evaluation which is PSNR,RMSE,MAE and SSIM was relatively allowable.

• Korean Journal of Remote Sensing
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• v.18 no.4
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• pp.221-231
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• 2002

In this study we applied a DEM generation algorithm developed in-house to satellite images at various resolution and discussed the results. We tested SPOT images at l0m resolution, EOC images at 6.6m and IKONOS images at 1m resolution. These images include the same urban area in Daejeon city. For camera model, we used Gupta & Hartley's(1997) DLT model for all three image sets. We carried out accuracy assessment using USGS DTED for SPOT and EOC and 23 check points for IKONOS. The assessment showed that SPOT DEM had about 38m RMS error, EOC DEM 12m RMS error and IKONOS DEM 6.5m RMS error. In terms of image resolution, SPOT and EOC DEM error corresponds to 2∼4 pixels where as IKONOS DEM error 6∼7pixels. IKONOS DEM contains more errors in pixels. However, in IKONOS DEM, individual buildings, apartments and major roads are identifiable. All three DEMs contained errors due to height discontinuity, occlusion and shadow. These experiments show that our algorithm can generate urban DEM from 1m resolution and that, however, we need to improve the algorithm to minimize effects of occlusion and building shadows on DEMs.

• Korean Journal of Remote Sensing
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• v.20 no.4
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• pp.235-244
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• 2004

This study focuses on the assessment for proposed algorithm to discriminate cloudy pixels from snowy pixels through use of visible, near infrared, and short wave infrared channel data in VEGETATION-1 sensor embarked on SPOT-4 satellite. Traditional threshold algorithms for cloud and snow masks did not show very good accuracy. Instead of these independent masking procedures, K-Means clustering scheme is employed for cloud/snow discrimination in this study. The pixels used in clustering were selected through an integration of two threshold algorithms, which group ensemble the snow and cloud pixels. This may give a opportunity to simplify the clustering procedure and to improve the accuracy as compared with full image clustering. This paper also compared the results with threshold methods of snow cover and clouds, and assesses discrimination capability in VEGETATION channels. The quality of the cloud and snow mask even more improved when present algorithm is implemented. The discrimination errors were considerably reduced by 19.4% and 9.7% for cloud mask and snow mask as compared with traditional methods, respectively.