• Proceedings of the KSRS Conference
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• v.1
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• pp.163-165
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• 2006

We aim to archive all the satellite images that had been scattered into Satellite Imagery Information System with setting naming rules and metadata. More than one million of scenes were collected, rectified into error-free status with metadata . Converting various formats into HDF format after considering GEOTIFF and HDF. Intranet and Internet System had been development to allow all the images to be searched and downloaded with less effort. These system will expand the usage of meteorological satellite images for expert groups and the public outside of KMA.

• Journal of Broadcast Engineering
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• v.13 no.2
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• pp.236-244
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• 2008

We propose a new building detection and description algorithm for Lidar data and photogrammetric imagery using color segmentation, line segments matching, perceptual grouping. Our algorithm consists of two steps. In the first step, from the initial building regions extracted from Lidar data and the color segmentation results from the photogrammetric imagery, we extract coarse building boundaries based on the Lidar results with split and merge technique from aerial imagery. In the secondstep, we extract precise building boundaries based on coarse building boundaries and edges from aerial imagery using line segments matching and perceptual grouping. The contribution of this algorithm is that color information in photogrammetric imagery is used to complement collapsed building boundaries obtained by Lidar. Moreover, linearity of the edges and construction of closed roof form are used to reflect the characteristic of man-made object. Experimental results on multisensor data demonstrate that the proposed algorithm produces more accurate and reliable results than Lidar sensor.

• Proceedings of the KSRS Conference
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• v.1
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• pp.413-416
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• 2006

As even small features can be classified as high resolution imagery, urban remote sensing is regarded as one of the important application fields in time of wide use of the commercialized high resolution satellite imageries. In this study, we have analyzed the variogram properties of high resolution imagery, which was obtained in urban area through the simple modeling and applied to the real image. Based on the grasped variogram characteristics, we have tried to decomposed two high-resolution imagery such as IKONOS and QuickBird reducing window size until the unique variogram that urban feature has come out and then been indexed. Modeling results will be used as the fundamental data for variographic analysis in urban area using high resolution imagery later on. Index map also can be used for determining urban complexity or land-use classification, because the index is influenced by the feature size.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.241-244
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• 2005

Many building detection methods mainly rely on line segments extracted from aerial or satellite imagery. Building detection methods based on line segments, however, are difficult to succeed in high resolution satellite imagery such as IKONOS imagery, for most buildings in IKONOS imagery have small size of roofs with low contrast between roof and background. In this paper, we propose an efficient method to extract line segments and group them at the same time. First, edge preserving filtering is applied to the imagery to remove the noise. Second, we segment the imagery by watershed method, which collects the pixels with similar intensities to obtain homogeneous region. The boundaries of homogeneous region are not completely coincident with roof boundaries due to low contrast in the vicinity of the roof boundaries. Finally, to resolve this problem, we set up snake model with segmented region boundaries as initial snake's positions. We used a greedy algorithm to fit a snake to roof boundary. Experimental results show our method can obtain more .correct roof boundary with small size and low contrast from IKONOS imagery. Snake algorithm, building roof detection, watershed segmentation, edge-preserving filtering

• Journal of International Academy of Physical Therapy Research
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• v.1 no.2
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• pp.155-161
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• 2010

Purpose: The purpose of this study was to estimate the effects of subliminal music with balance imagery training on balance and concentration. Methods: The participants were 45 seniors in an undergraduate school in Korea. The subliminal music with balance imagery training intervention was carried out for 20 minutes. Other interventions were also carried out for 20 minutes. 12 seniors(Group A) listened to subliminal music with balance imagery training, 12 seniors(Group B) listened to subliminal music, 11 seniors(Group C) received balance imagery training, and 10 seniors(Group D) had no intervention(Control group). The grid test is related to measured levels of concentration intensity. Romberg one legged standing test was carried out for 30 seconds. The collected data was analyzed by one-paired t test and one way ANOVA using the SPSS Windows 12 ver. program. Results: The major findings of this study were as follows: Concentration levels of Group A and C improved, and balance levels of Group C and D improved. There was a statistically significant decrease in concentration between Group A and B, Group A and C after intervention. Conclusion: These findings suggest that listening to subliminal music with balance imagery training may be useful in managing concentration in seniors. So it provides basic information for further concentration on improving education on music with balance imagery training.

• The Journal of Economics, Marketing and Management
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• v.12 no.6
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• pp.27-39
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• 2024

Purpose: Short-form travel video plays a significant role in promoting the development of the global tourism industry and the recovery of tourism after prolonged health crises. However, only a limited number of studies have explored the specific influence of short-form video tourism content on individuals' travel behavioral intentions particularly from the perspectives of mental imagery formation and information processing fluency. This study bridges this gap by integrating the theory of mental imagery with processing fluency, applying these concepts to the domains of tourism and short-form video research. Research design, data and methodology: Data were gathered using a web-based survey method with Chinese short-form video users (N=390). Structural Equation Modelling (SEM), and Analysis of Variance (ANOVA) were employed to assess the research model and test the hypotheses. Results: This study examines the structural influence of comprehension fluency and imagery fluency, which act as both direct and indirect antecedents to mental imagery elaboration, ultimately shaping individuals' intentions to visit a destination. Conclusions: This study delves deeper into the role of processing fluency in mental imagery, addressing the gaps in existing research on the "processing fluency-mental imagery" framework. The findings provide both theoretical and practical insights into how individuals process short-form travel video and how this processing influences their intentions regarding travel behavior.

• Spatial Information Research
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• v.9 no.1
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• pp.31-50
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• 2001

This study has analyzed GeoTIFF, SDTS, HDF, and BIIF as the representative formats of spatial imagery information with two parts. First is to compare 4 formats with each other based on 4 comparison criteria (extensibility, interchangeability, current widespread use, long-term stability) by analyzing specification of each format. Second is to estimate current use and interchangeability of 4 formats between 5 commercial softwares used commonly. The result shows that GeoTIFF is currently better than three other formats. However, the more various spatial imagery information are and the larger capacity they have, the more formats are developed and updated, which means that only one format should not be considered as a standard format continuously. It is better to provide a standard format proper to the time through continuous research and sustainable policy support should be followed.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.59-64
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• 2002

This paper presents a method for line segment extraction for 3-d building reconstruction. Building roofs are described as a set of planar polygonal patches, each of which is extracted by watershed-based image segmentation, line segment matching and coplanar grouping. Coplanar grouping and polygonal patch formation are performed per region by selecting 3-d line segments that are matched using epipolar geometry and flight information. The algorithm has been applied to high resolution aerial images and the results show accurate 3-d building reconstruction.

• Korean Journal of Remote Sensing
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• v.21 no.5
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• pp.383-392
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• 2005

Vegetation classes, especially grass and tree classes, are often confused in classification when conventional spectral pattern recognition techniques are used to classify urban areas. This paper reports on a study to improve the classification results by using an automated process of considering height information in separating urban vegetation classes, specifically tree and grass, using three-band, high-spatial resolution, digital aerial imagery. Height information was derived photogrammetrically from stereo pair imagery using cross correlation image matching to estimate differential parallax for vegetation pixels. A threshold value of differential parallax was used to assess whether the original class was correct. The average increase in overall accuracy for three test stereo pairs was $7.8\%$, and detailed examination showed that pixels reclassified as grass improved the overall accuracy more than pixels reclassified as tree. Visual examination and statistical accuracy assessment of four test areas showed improvement in vegetation classification with the increase in accuracy ranging from $3.7\%\;to\;18.1\%$. Vegetation classification can, in fact, be improved by adding height information to the classification procedure.

• Korean Journal of Remote Sensing
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• v.27 no.6
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• pp.717-728
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• 2011

An efficient method for the unsupervised classification of high resolution imagery is suggested in this paper. It employs pixel-linking and merging based on the adjacency graph. The proposed algorithm uses the neighbor lines of 8 directions to include information in spatial proximity. Two approaches are suggested to employ neighbor lines in the linking. One is to compute the dissimilarity measure for the pixel-linking using information from the best lines with the smallest non. The other is to select the best directions for the dissimilarity measure by comparing the non-homogeneity of each line in the same direction of two adjacent pixels. The resultant partition of pixel-linking is segmented and classified by the merging based on the regional and spectral adjacency graphs. This study performed extensive experiments using simulation data and a real high resolution data of IKONOS. The experimental results show that the new approach proposed in this study is quite effective to provide segments of high quality for object-based analysis and proper land-cover map for high resolution imagery of urban area.