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Comparison of Texture Images and Application of Template Matching for Geo-spatial Feature Analysis Based on Remote Sensing Data  

Yoo Hee Young (Department of Earth Science Education, Seoul National University)
Jeon So Hee (Department of Earth Science Education, Seoul National University)
Lee Kiwon (Department of Information Systems, Hansung University)
Kwon Byung-Doo (Department of Earth Science Education, Seoul National University)
Publication Information
Journal of the Korean earth science society / v.26, no.7, 2005 , pp. 683-690 More about this Journal
Abstract
As remote sensing imagery with high spatial resolution (e.g. pixel resolution of 1m or less) is used widely in the specific application domains, the requirements of advanced methods for this imagery are increasing. Among many applicable methods, the texture image analysis, which was characterized by the spatial distribution of the gray levels in a neighborhood, can be regarded as one useful method. In the texture image, we compared and analyzed different results according to various directions, kernel sizes, and parameter types for the GLCM algorithm. Then, we studied spatial feature characteristics within each result image. In addition, a template matching program which can search spatial patterns using template images selected from original and texture images was also embodied and applied. Probabilities were examined on the basis of the results. These results would anticipate effective applications for detecting and analyzing specific shaped geological or other complex features using high spatial resolution imagery.
Keywords
texture image; GLCM; template matching;
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