@inproceedings{58781065cfe0413096e94613085d15ab,
title = "An aerial image data cleaning of power lines with multi-information fusion perception",
abstract = "Recently, unmanned aerial vehicles (UAVs) have been used to conduct the task of power line inspection. Unfortunately, most of the images acquired by UAVs are invalid for visual inspection. The main reason is that the collected images are low quality and repetitive. To obtain a set of valid images with high quality, a novel multi-information fusion perception (MIFP) model is proposed to automatically clean the large-scale aerial image data. Firstly, the image quality features and image content features are extracted, in which the weights of different features are used to evaluate the effect on the final image quality. Secondly, the image spatial features are exploited to aggregate spatial information in weight maps of different sizes. Then, the image quality and content features are merged into the multi-information features that characterize the quality of the final image. As a result, the image is picked out according to the quality score. Finally, experimental results show that the proposed multi information fusion perception model has excellent performance on real databases.",
keywords = "Data cleaning, deep learning, image quality assessment, power line inspection",
author = "Yanjun Fan and Qian Yang and Yangming Guo and Lujuan Jiang and Jiang Long and Zhuqing Wang and Guo Li",
note = "Publisher Copyright: {\textcopyright} 2022 SPIE.; 3rd International Conference on Computer Science and Communication Technology, ICCSCT 2022 ; Conference date: 30-07-2022 Through 31-07-2022",
year = "2022",
doi = "10.1117/12.2662509",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Yingfa Lu and Changbo Cheng",
booktitle = "Third International Conference on Computer Science and Communication Technology, ICCSCT 2022",
}