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Advances in Multi-Sensor Data Fusion: Algorithms and Applications
Data Center for Resources and Environmental Sciences, State Key Lab of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
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Received: 30 June 2009; in revised form: 13 August 2009 / Accepted: 17 September 2009 / Published: 30 September 2009
Abstract: With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of “algorithm fusion” methods; (3) Establishment of an automatic quality assessment scheme.
Keywords: multi-sensor; data fusion; remote sensing
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MDPI and ACS Style
Dong, J.; Zhuang, D.; Huang, Y.; Fu, J. Advances in Multi-Sensor Data Fusion: Algorithms and Applications. Sensors 2009, 9, 7771-7784.
Dong J, Zhuang D, Huang Y, Fu J. Advances in Multi-Sensor Data Fusion: Algorithms and Applications. Sensors. 2009; 9(10):7771-7784.
Dong, Jiang; Zhuang, Dafang; Huang, Yaohuan; Fu, Jingying. 2009. "Advances in Multi-Sensor Data Fusion: Algorithms and Applications." Sensors 9, no. 10: 7771-7784.