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Vision-based aerial image mosaicking algorithm with object detection

Journal of Systems Engineering and Electronics 2022年第2期33卷 259-268页

作者： HAN Jun LI Weixing FENG Kai PAN Feng School of Automation Beijing Institute of TechnologyBeijing 100081China

Aerial image sequence mosaicking is one of the chal-lenging research fields in computer *** obtain large-scale orthophoto maps with object detection information,we propose a vision-based image mosaicking algorithm without any extra location *** to object detection results,we define a complexity factor to describe the importance of each input ima-ge and dynamically optimize the feature extraction *** 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 ***,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 *** proposed algorithm is performed by using multithreading and graphics processing unit(GPU)accel-eration on several aerial image *** experiment results demonstrate that our algorithm outperforms most of the existing aerial image mosaicking methods in visual quality while guaranteeing a high calculation speed.

关键词： image mosaicking object detection grid motion statistic(GMS) mapping

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Damage quantitative assessment of spacecraft in a large-size inspection

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Frontiers of Information Technology & Electronic Engineering 2022年第4期23卷 542-554页

作者： Kuo ZHANG Jianliang HUO Shengzhe WANG Xiao ZHANG Yiting FENG School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu611731China Norla Institute of Technical Physics Chengdu610041China

To ensure the safety and reliability of spacecraft during multiple space missions,it is necessary to conduct in-situ nondestructive detection of the spacecraft to judge the damage caused by the hypervelocity impact of micrometeoroids and orbital debris(MMOD).In this paper,we propose an innovative quantitative assessment method based on damage reconstructed image mosaic ***,a Gaussian mixture model clustering algorithm is applied to extract images that highlight damage ***,a mosaicking scheme based on the ORB feature extraction algorithm and an improved M-estimator SAmple Consensus(MSAC)algorithm with an adaptive threshold selection method is proposed which can create large-scale mosaicked images for damage ***,to create the mosaicked images,the damage characteristic regions are segmented and *** location of the damage area is determined and the degree of damage is judged by calculating the centroid position and the perimeter quantitative *** efficiency and applicability of the proposed method are verified by the experimental results.

关键词： Hypervelocity impact Damage information extraction image mosaicking Damage localization Quantitative assessment

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