
Proceedings Paper
Multisource remote sensing image fusion based on curvelet and wavelet transformFormat | Member Price | Non-Member Price |
---|---|---|
$17.00 | $21.00 |
Paper Abstract
Aiming at limitations of existing multiresolution analysis (MRA) fusion methods, this paper proposes a new fusion
method which combines curvelet and wavelet transform. Curvelet transform processes edges better than wavelet
transform does. While wavelet transform handles smooth area better than curvelet transform does. As an image often
includes more than one feature, the proposed method is conducted on the basis of region segmentation and use Àtrous
wavelet transform (ATWT) to fuse smooth areas and fast discrete curvelet transform (FDCT) to fuse areas with edges.
Furthermore, an optimal objective function defined based on a balance between spectral preservation and spatial
resolution improvement is put forward to search optimal segmentation threshold. The optimal fusion result can be
obtained by fusion processing through the optimal segmentation threshold. Landsat TM multispectral (MS) images and
SPOT Panchromatic (Pan) image covering a region of Wuhan in Hubei province are tested to assess this proposed
method. Visual evaluation and statistics analysis are employed to assess the quality of fused images of different methods.
The proposed method demonstrates best results among methods being tested in this study. So by combining attributes of
both transforms, it is possible to get better image fusion result than by using wavelet and curvelet individually.
Paper Details
Date Published: 23 November 2011
PDF: 6 pages
Proc. SPIE 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 80060P (23 November 2011); doi: 10.1117/12.901815
Published in SPIE Proceedings Vol. 8006:
MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Faxiong Zhang; Faxiong Zhang, Editor(s)
PDF: 6 pages
Proc. SPIE 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 80060P (23 November 2011); doi: 10.1117/12.901815
Show Author Affiliations
Moyan Xiao, Hubei Univ. of Education (China)
Zhibiao He, Wuhan Univ. (China)
Published in SPIE Proceedings Vol. 8006:
MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Faxiong Zhang; Faxiong Zhang, Editor(s)
© SPIE. Terms of Use
