Integration of Spatial Chaotic Model and Type-2 Fuzzy Sets to Coastline Detection in SAR images

• Main Authors: Jing-Yi Chen, 陳靜儀
• Other Authors: none
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/91558200365030074780

碩士 === 國立聯合大學 === 電子工程學系碩士班 === 96 === In this study, an edge detector which integrates the spatial chaotic model (SCM) and type-2 fuzzy sets for coastline detection in synthetic aperture radar (SAR) images is proposed. It has already been recognized that ocean areas in SAR images are almost always much lower in grey levels than land areas. Therefore, image segmentation approach can be very useful for ocean-land separation. An SAR signal presents a chaotic phenomenon which results from coherent energy imaging. Therefore, an SAR signal is modeled by the SCM and characterized by its fractal dimension which is estimated by the differential box-counting (DBC) technique. Observations provided by SAR sensors are uncertain due to changing illumination conditions at different acquiring time. Besides, the selection of window size M and grid size s in DBC provides an additional degree of uncertainty. Both the uncertainty involved in the measurements and the uncertainty involved in the selection of M and s motivate us of integrating type-2 fuzzy sets with the SCM to achieve a better performance. The proposed approach is applied to SAR images for coastline detection as demonstrations.