The Application Of The Minimum Noise Fraction Transform To The Compression And Cleaning Of Hyper-spectral Remote Sensing Data

Author(s):  
A.A. Green ◽  
M.D. Craig ◽  
Cheng Shi
2015 ◽  
Vol 13 (1) ◽  
pp. 187-200 ◽  
Author(s):  
L. Luft ◽  
C. Neumann ◽  
S. Itzerott ◽  
A. Lausch ◽  
D. Doktor ◽  
...  

2015 ◽  
Vol 35 (24) ◽  
Author(s):  
章文龙 ZHANG Wenlong ◽  
曾从盛 ZENG Congsheng ◽  
高灯州 GAO Dengzhou ◽  
陈晓艳 CHEN Xiaoyan ◽  
林伟 LIN Wei

2005 ◽  
Vol 42 (12) ◽  
pp. 2173-2193 ◽  
Author(s):  
J R Harris ◽  
D Rogge ◽  
R Hitchcock ◽  
O Ijewliw ◽  
D Wright

A test site in southern Baffin Island, Canada has been established to study the applications of hyperspectral data to lithological mapping. Good bedrock exposure and minimal vegetation cover provide an ideal environment for the evaluation of hyperspectral remote sensing. Airborne PROBE hyperspectral data were collected over the study site during the summer of 2000. Processing methods involved (1) applying a minimum noise fraction (MNF) transformation to the data and visual interpretation of a ternary colour MNF image to produce a lithological–compositional map, and (2) selection of end members from the MNF image followed by matched filtering based on the selected end members to produce a lithological–compositional map. Both methods have produced a lithological map that compares favourably with the existing geological map. Although lichen imparts a similarity to the spectra throughout the visible and near infrared and short-wave infrared ranges, this study has shown that enough variability in the spectra as a function of different mineralogy was present to successfully discriminate one major lithological group (metatonalites) and three compositional units (psammites, quartzites, and monzogranites). Vegetation could be clearly distinguished, which in this area only is a good proxy for mapping metagabbroic rocks. Furthermore, discrimination of slightly different compositional units within the psammites and the metatonalites was also possible. The results from this study indicate that hyperspectral remotely sensed imagery holds promise for lithological mapping in Canada's North, although further analysis is required in different geologic environments in Canada's North to validate hyperspectral remote sensing as a useful aid to litho logical mapping.


2014 ◽  
Vol 1073-1076 ◽  
pp. 1972-1976
Author(s):  
Jie Zhang ◽  
Hao Yan Zhao ◽  
Min Xia Zhang

With 3S comprehensive analysis on vegetation and the further development of hyper-spectral technology, the dynamic monitor of large area vegetation in long-term has become the trend. Intelligent process, combined the remote sensing data and field data, constructing dynamic monitoring model, plays an important guilding role in ecological security and balance. By using hyper-spectral remote sensing data of desert vegetation, three groups of spectral characteristic parameters were selected as input data of typical desert vegetation in the research, and vegetation types were selected as output data. Typical vegetation classifier was constructed based on the BP neural network model to study the vegetation classification.


2014 ◽  
Vol 644-650 ◽  
pp. 1085-1088 ◽  
Author(s):  
Guang Yang ◽  
Zhong Xiang Lei ◽  
He Nan Wu ◽  
Qiang Qiang Meng ◽  
Gao Pan He

A novel method was proposed to solve the problem which was caused by high dimensions. Minimum Noise Fraction was used for dimension reduction. And then the RX algorithm and KRX algorithm was used to detect the data after dimensional reduction. The method proposed was better by comparing the ROC of four detection results.


Sign in / Sign up

Export Citation Format

Share Document