Vision-based aerial image mosaicking algorithm with object detection

作     者：HAN Jun LI Weixing FENG Kai PAN Feng HAN Jun;LI Weixing;FENG Kai;PAN Feng

作者机构：School of AutomationBeijing Institute of TechnologyBeijing 100081China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2022年第33卷第2期

页      面：259-268页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 081002[工学-信号与信息处理] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Foundation of China(61603040 61973036). 

主　　题：image mosaicking object detection grid motion statistic(GMS) mapping 

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.