November 2022
Intermediate
608 pages
21h 38m
English
Content preview from Advances in Hyperspectral Image Processing Techniques
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11Hyperspectral Data Fusion Using Multidimensional Information
Lifu Zhang1, Xia Zhang1, Mingyuan Peng2, Xuejian Sun1, and Xiaoyang Zhao1,3
1Hyperspectral Remote Sensing Application Division, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
2Land Satellite Remote Sensing Application Center, MNR, Beijing, China
3College of Natural Resources and Environment, University of Chinese Academy of Sciences, Beijing, China
11.1 Introduction of Remote Sensing Data Fusion
11.1.1 Basic Idea of Data Fusion
Data fusion is the process of synthesizing different indicators or data from different sources through some algorithms to obtain richer information than that from a single data source. According to the type of fusion data source, remote sensing data fusion can be divided into homogeneous remote sensing data fusion (remote sensing data to be fused is obtained by the same imaging method, and the main purpose is to improve the temporal, spatial, and spectral resolution of data); heterogeneous remote sensing data fusion (remote sensing data to be fused is obtained by different imaging means, such as optical‐thermal infrared and optical‐radar data); remote sensing‐site data fusion (fusion of large‐area low‐precision remote sensing data and high‐precision site observation data is to obtain continuous, high‐precision, and large area surface data); remote sensing‐non‐observation data fusion (remote sensing data and non‐remote sensing observation data are fused, ...
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