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