@misc{Song_Zhehan_Real_2022,
 author={Song, Zhehan and Feng, Huajun and Xu, Zhihai and Li, Qi},
 contributor={Urbańczyk, Wacław. Redakcja},
 identifier={DOI: 10.37190/oa220208},
 year={2022},
 rights={Wszystkie prawa zastrzeżone (Copyright)},
 publisher={Oficyna Wydawnicza Politechniki Wrocławskiej},
 description={Optica Applicata, Vol. 52, 2022, nr 2, s. 259-272},
 description={Optica Applicata is an international journal, published in a non-periodical form in the years 1971-1973 and quarterly since 1973. From the beginning of the year 2008, Optica Applicata is an Open Access journal available online via the Internet, with free access to the full text of articles serving the best interests of the scientific community. The journal is abstracted and indexed in: Chemical Abstracts, Compendex, Current Contents, Inspec, Referativnyj Zhurnal, SCI Expanded, Scopus, Ulrich’s Periodicals Directory},
 description={http://opticaapplicata.pwr.edu.pl/},
 language={eng},
 abstract={When cameras are used in aerial photography, satellite imaging or other scenes, the motion of the observational target causes image blur. The corresponding motion compensation systems often present some response delay. Thus, we introduce effective and fast motion prediction for the target to achieve steady real-time motion compensation. We first analyze the target motion states to propose a fast and robust prediction method based on the least square support vector machine algorithm. Then, we evaluate the performance between ours and other state-of-the-art methods through experiments. Experimental results confirm that the proposed method provides a fast and robust prediction for target motion. At last, we embed our method with dual-resolution camera system to perform high-quality motion compensation effect in real time.},
 type={artykuł},
 title={Real time motion compensation technology based on least square support vector machine prediction},
 keywords={optyka, motion compensation, motion prediction, dual-resolution camera system, least square support vector machine},
}