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The Study on Optimal Image Processing and Identifying Threshold Values for Enhancing the Accuracy of Damage Information from Natural Disasters  

Seo, Jung-Taek (인하대학교 공과대학 지리정보공학과)
Kim, Kye-Hyun (인하대학교 공과대학 지리정보공학과)
Publication Information
Spatial Information Research / v.19, no.5, 2011 , pp. 1-11 More about this Journal
Abstract
This study mainly focused on the method of accurately extracting damage information in the im agery change detection process using the constructed high resolution aerial im agery. Bongwha-gun in Gyungsangbuk-do which had been severely damaged from a localized torrential downpour at the end of July, 2008 was selected as study area. This study utilized aerial im agery having photographing scale of 30cm gray image of pre-disaster and 40cm color image of post-disaster. In order to correct errors from the differences of the image resolution of pre-/post-disaster and time series, the prelim inary phase of image processing techniques such as normalizing, contrast enhancement and equalizing were applied to reduce errors. The extent of the damage was calculated using one to one comparison of the intensity of each pixel of pre-/post-disaster im aged. In this step, threshold values which facilitate to extract the extent that damage investigator wants were applied by setting difference values of the intensity of pixel of pre-/post-disaster. The accuracy of optimal image processing and the result of threshold values were verified using the error matrix. The results of the study enabled the early exaction of the extents of the damages using the aerial imagery with identical characteristics. It was also possible to apply to various damage items for imagery change detection in case of utilizing multi-band im agery. Furthermore, more quantitative estimation of the dam ages would be possible with the use of numerous GIS layers such as land cover and cadastral maps.
Keywords
Damage Investigation; Aerial Image; Image Change Detection; Image Processing; Threshold;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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