DocumentCode :
3235362
Title :
A new algorithm for DEM data compression base on feature points
Author :
Feng, Qi ; Xiao, Qiao
Author_Institution :
Sch. of Electron. & Inf., Northwestern Polytech. Univ., Xi´´an, China
fYear :
2011
fDate :
27-29 May 2011
Firstpage :
326
Lastpage :
329
Abstract :
To take full advantage of topography characteristic and improve compression ratio when compressing digital elevation model(DEM), a new compression method based on BP neural network is proposed. An extraction algorithm of feature points including terrain ridge line and valleys is given firstly. Then the BP neural network is trained to implement DEM compression by using the extracted feature points. The experimental results demonstrate the effectiveness of presented method, which can enhance DEM compression effect.
Keywords :
backpropagation; data compression; digital elevation models; feature extraction; neural nets; BP neural network; DEM; data compression; digital elevation model; feature point extraction; topography characteristic; Artificial neural networks; Educational institutions; Niobium; BP neural network; DEM; compression; feature points extraction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-61284-485-5
Type :
conf
DOI :
10.1109/ICCSN.2011.6014452
Filename :
6014452
Link To Document :
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