Advances in Multi-Sensor Data Fusion: Algorithms and Applications
By Jiang Dong, D. Zhuang, Yaohuan Huang, Jingying Fu. Italian National Conference on Sensors, 2009
347 citations recorded by the source corpus.
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.
Subfields: Media Technology, Ocean Engineering
View Paper: https://www.semanticscholar.org/paper/2d7e4306a1f7ea9242db72639479db08e18f7b26
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
Citations in the corpus
- From Data Acquisition to Data Fusion: A Comprehensive Review and a Roadmap for the Identification of Activities of Daily Living Using Mobile Devices (2016, methodology): “Distributed systems for sensor data fusion with off-the-shelf mobile devices have been used for tracking [120–122, In [152], several types of sensors (e.g., complementing the detection of objects using a camera and inertial sensors) are used to classify objects and detect changes.”