• Korean Journal of Remote Sensing
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• 제38권6_1호
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.

• Journal of the Korean Geographical Society
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• 제30권1호
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• pp.57-67
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• 1995

The study on the factorial ecology of the residential patterns is to provide one of the yardsticks for description and comparison of urban structures. Many Korean geographers have adopted this method to analyse the urban structure of Korean cities. According to these studies, one of the main factors in Korean cities in large and middle sizes is family status. The spatial pattern of family status is zonal, similar to the cases of Japanese and Western cities. The age is one of the principal indices of familyf status, hence the author chose the age composition to analyse the residential patten. This Paper is to describe the residential segreagation pattern due to age composition and recent pattern changes in the Cheongju city, and than to explain the reason for these changes. All data are derived from the Population Censuses of Korea for 1970, 1980 and 1990. Eighteen groups of age with five-year interval (0-4, 5-9, 10-14, 15-19, 20-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75-79, 80-84, 85- and- over) are adopted here. Unit area for this analysis is administrative district(Dong) within Cheonaju city. District are classified into smaller groups based on the similarity of age composition, using the method of cluster analysis. The main findings are summarized as follows: 1. Population have increased remarkably in the eastern reaion neighboring CBD of Cheongju city in 1970's. And in western region from CBD new residential area have developed in 1980's. 2. Spatial pattarns showed a concentric circle type in central district and its neighbor regions and a sector type in periphery regions in 1970; a cirele type in central district and a sector typesin neighbor regions and periphery regions in 1980 and 1990. Thess residential pattern play an important role in the population composition ratio of younger aged group (l5-34) and older aged group (65-and-over). 3. Spatial change of types by age composition showed the higher ratio of groups of 0-9 and 35-49, and lower ratio of group 20-24 in 1970's. Dominent groups are ratio of 0-14, 40-49, 55-64, 7O-79, and 85- and- over in 1980's. These changes mainly appeared in central district and periphery regions. 4. The reasons for the change of age composition was the development of msnufacturing industries with the increase of population and new construction of residential areas both in the neighbor regions of cnetral district and periphery regions. These phenomena were caused by immigration of younger aged groups and increasing of residents of aged groups in these regions.

• The Journal of Korean Society for Radiation Therapy
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• 제19권2호
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• pp.113-122
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• 2007

Purpose: We proposed the method using dose-volume Histogram index to compare prospective plan trials in tomotherapy planning optimization. Materials and Methods: For 3 patients in cranial region, thorax and abdominal region, we acquired computed tomography images with PQ 5000 in each case. Then we delineated target structure and normal organ contour with pinnacle Ver 7.6c, after transferred each data to tomotherapy planning system (hi-art system Ver 2.0), we optimized 3 plan trials in each case that used differ from beam width, pitch, importance. We analyzed 3 plan trials in each region with isodose distribution, dose-volume histogram and dose statistics. Also we verified 3 plan trials with specialized DVH-indexes that is dose homogeneity index in target organ, conformity index around target structure and dose gradient index in non-target structures. Results: We compared with the similarity of results that the one is decide the best plan trial using isodose distribution, dose volume histogram and dose statistics, and the another is using DVH-indexes. They all decided the same plan trial to better result in each case. Conclusion: In some of case, it was appeared a little difference of results that used to DVH-index for comparison of plan trial in tomotherapy by special goal in it. But because DVH-index represented both dose distribution in target structure and high dose risk about normal tissue, it will be reasonable method for comparison of many plan trials before the tomotherapy treatments.