Vision-based aerial image mosaicking algorithm with object detection

• 作者: HAN Jun LI Weixing FENG Kai PAN Feng
• 来源期刊: 系统工程与电子技术（英文版）
• 年，卷（期）: 2022,（2）
• 所属期刊栏目: ELECTRONICS TECHNOLOGY
• 页码范围: 259-268
• 页数: 10页
• 语种: 英文
• DOI: 10.23919/JSEE.2022.000026

摘要

Aerial image sequence mosaicking is one of the chal-lenging research fields in computer vision. To obtain large-scale orthophoto maps with object detection information, we propose a vision-based image mosaicking algorithm without any extra location data. According to object detection results, we define a complexity factor to describe the importance of each input ima-ge and dynamically optimize the feature extraction process. The feature points extraction and matching processes are mainly guided by the speeded-up robust features (SURF) and the grid motion statistic (GMS) algorithm respectively. A robust refer-ence frame selection method is proposed to eliminate the trans-formation distortion by searching for the center area based on overlaps. Besides, the sparse Levenberg-Marquardt (LM) al-gorithm and the heavy occluded frames removal method are ap-plied to reduce accumulated errors and further improve the mo-saicking performance. The proposed algorithm is performed by using multithreading and graphics processing unit (GPU) accel-eration on several aerial image datasets. Extensive experiment results demonstrate that our algorithm outperforms most of the existing aerial image mosaicking methods in visual quality while guaranteeing a high calculation speed.