A study of using Scale Invariant Feature Transform (SIFT) algorithm for radar satellite imagery coregistration

• Main Authors: Chtng-Yuan Teng, 鄧景元
• Other Authors: Chung-Ru Ho
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/84739806805595993983

碩士 === 國立臺灣海洋大學 === 海洋環境資訊學系 === 98 === The time-sequence images are collected on different orbits and incidence angles, results in images are quite different in scale, position and rotation angle. That will be a problem when one tries to locate interest points on different images and match them. Besides, radar reflectance highly depends on the local incidence angle with terrain and the shape of the object; it is harder to match radar imagery. Therefore, how to automatically register radar imagery has become a critical issue. In this thesis, we study the radar imaging geometry, radar imagery characteristics, and differentiations between images like variance in scale and rotation. Scale Invariant Feature Transformation (SIFT) has been proven to match optical imagery with variance in scale, translation and rotation. After a thorough study, we try to use SIFT on radar imagery to get stable features automatically to avoid the influence of imagery shift, scale and speckles in time-sequence images, without user intervention. According to the result via testing SIFT on several pair radar images with different resolution and imaging angle. These shows that SIFT can locate interest points on the roads and building in the image and match them accurately. Therefore, SIFT can register different radar imagery effectively and automatically.