Automatic control points between images to select the analysis and application of optimization strategies

• Main Authors: Liang-Hung Liu, 劉亮宏
• Other Authors: Liang-Hwei Lee
• Format: Others
• Language: zh-TW
• Published: 101
• Online Access: http://ndltd.ncl.edu.tw/handle/31122079919113479657

碩士 === 國立高雄應用科技大學 === 土木工程與防災科技研究所 === 100 === The core work of the Geospatial Information is to derive the earth surface 3D information from the stereogram of EO(Earth Observation) satellite and to rebuild the DEM(Digital Elevation Model). The critical technology of the image registration still uses traditional area basic matching to process pixel identification, point detection, and position measurement. In order to achieve automatically points detection and reach the high precision of sub-pixel, a pack of sufficient feature points of the image are the requirement to process image registration and ground truth position, etc. With the fast development of the remote sensing, there are more and more images can be gathered by multi-period, multi-source, and multi-resolution. However, these images are faced the difficulty of image registration due to displacement, rotation, scale, topology, and panorama of the images. In order to minimize the affine distortion of a pair of images which are affected by displacement, rotation, scale, topology, and panorama, these tow images have to find a pack of even distributed, sufficient, high precise points. Therefore, a better image registration method can not only minimize the differential of the scale and rotation but also improve the efficiency and resolution of the image registration. This thesis addresses the optimal strategy of automatically detection for control points is using the feature matching and are matching of the Voronoi-Delaynay method to automatically predict the position points by point. To automatically derive feature points in different period and different source images, the conjugate principal points and quote the feature matching algorithm is provided to analyze the differential of the feature points. The resolution of the sub-pixel can be reached and the results can be the reference for next images.