In January 17th, 2 (Shen Huanfeng: single source and multi-source image quality improvement method) in the academic report of.
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Report title: single source and multi-source image quality improvement method
Date and time of the report: 2015, 17, 01Saturday morning 9:30
Report location： Computer Institute-403
Speaker: Dr. Shen Huanfeng
Report of Nationality: China
The report of people: Wuhan University
Lecture 1: Dr. Shen Huanfeng, male, born in 1980, Ph.D., Wuhan University Luojiashan scholar Professor, deputy director of the Geography Department of Information Engineering College of resources and environment scienceIEEE Senior member, the National Natural Science Foundation of China, the outstanding youth fund of Hubei Province, outstanding youth fund of province, was selected for the Ministry of education, the new century outstanding talent support program". The main research direction for the image quality improvement, integration and its application, has presided over the National Natural Science Fund 4, as the subject of the deputy head, second responsible person to take a number of 973, 863 issues. Published in the domestic and foreign research papers published more than 100 articles, including international image processing authority“IEEE Transactions on Image Processing”，Authoritative journals in the field of remote sensing“IEEE Transactions on Geoscience and Remote Sensing”, “Environment of Remote Sensing”52 papers, including the SCI, were cited 919 times.(Google Scholar Citations)，The single highest cited 180 times. 2 academic monographs, 7 national invention patents, as a special guest of 17 international journals
Abstract: because of the existence of the quality factor, the limitation of imaging parameters, and the limitation of the observation ability, the image data often appear to have poor imaging quality, which can not realize the accurate characterization of the target. In this report, we discuss the quality improvement of video and remote sensing image based on its own research. The main content includes the image super-resolution reconstruction, the quality of the image, the improvement strategy, the fusion of the time space spectrum image data, and the application of the image quality improvement.
Invite people: Professor Wu Libing
