DocumentCode
143986
Title
Automatic feature learning of SAR images for sea ice concentration estimation using feed-forward neural networks
Author
Lei Wang ; Scott, K. ; Clausi, David
Author_Institution
Dept. of Syst. Design Eng., Univ. of Waterloo, Waterloo, ON, Canada
fYear
2014
fDate
13-18 July 2014
Firstpage
3969
Lastpage
3971
Abstract
A two-layer feed forward neural network is used to estimate ice concentration from SAR images directly in this research. SAR image patches are used as input. The CIS (Canadian Ice Service) ice concentration image analyses are used to train the neural network. The experiment shows that the simple neural network can be used to generate a reasonable ice concentration with no preprocessing to the SAR images.
Keywords
feature extraction; geophysical image processing; neural nets; oceanographic techniques; remote sensing by radar; sea ice; synthetic aperture radar; CIS ice concentration image analysis; Canadian Ice Service; SAR image patches; SAR images; automatic feature learning; feed-forward neural networks; sea ice concentration estimation; Biological neural networks; Estimation; Image analysis; Sea ice; Synthetic aperture radar; SAR; neural network; regression; sea ice concentration;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location
Quebec City, QC
Type
conf
DOI
10.1109/IGARSS.2014.6947354
Filename
6947354
Link To Document