|
Published Articles >> Table of Contents >> Abstract
Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06)
pp. 588-593
Mallat Fusion for Multi-Source Remote Sensing Classification
Dongdong Cao, Beijing Normal University, China
Qian Yin, Beijing Normal University, China
Ping Guo, IEEE
Full Article Text:
 
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ISDA.2006.189
Send link to a friend
| Abstract |
|
The fusion of multi-source remote sensing
data is to offer improved accuracies in land cover
classification. The conventional fusion methods such as
HIS and PCA can not enhance information and
simultaneously preserve high fidelity. Thus, the fused
image is not preferable for classification. In this paper, the
multi-source remote sensing data fusion based on Mallat
algorithm for classification is proposed. The purpose of
fusion is to create a new image that is more suitable for
recognition. The topic focuses on the pyramid
decomposition and choosing coefficients in the fusion
process. The performance of proposed method is assessed
by statistical methods and its effectiveness also testified by
classification accuracies.
|
 Additional Information
|
Index Terms- Mallet fusion, Multi-source classification, Wavelet, Feature selection
Citation:
Dongdong Cao, Qian Yin, Ping Guo,
"Mallat Fusion for Multi-Source Remote Sensing Classification,"
isda,
pp. 588-593,
Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06),
2006
|
|
