Fusion of multispectral and panchromatic Satellite images using the curvelet transform

A useful technique in various applications of remote sensing involves the fusion of different types of satellite images, namely multispectral (MS) satellite images with a high spectral and low spatial resolution and panchromatic (Pan) satellite image with a low spectral and high spatial resolution....

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Bibliographic Details
Published in:IEEE geoscience and remote sensing letters 2005-04, Vol.2 (2), p.136-140
Main Authors: Choi, M., Kim, R.Y., Nam, M.-R., Kim, H.O.
Format: Article
Language:English
Subjects:
Curvelet transform
Data mining
Image fusion
Image resolution
Landsat Enhanced Thematic Mapper Plus (ETM+) image
Multiresolution analysis
Principal component analysis
Remote sensing
Satellites
Spatial resolution
Wavelet analysis
wavelet transform
Wavelet transforms
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Summary:A useful technique in various applications of remote sensing involves the fusion of different types of satellite images, namely multispectral (MS) satellite images with a high spectral and low spatial resolution and panchromatic (Pan) satellite image with a low spectral and high spatial resolution. Recent studies show that wavelet-based image fusion provides high-quality spectral content in fused images. However, the results of most wavelet-based methods of image fusion have a spatial resolution that is less than that obtained via the Brovey, intensity-hue-saturation, and principal components analysis methods of image fusion. We introduce an improved method of image fusion which is based on the amelioration de la resolution spatiale par injection de structures (ARSIS) concept using the curvelet transform, because the curvelet transform represents edges better than wavelets. Because edges are fundamental in image representation, enhancing the edges is an effective means of enhancing spatial resolution. Curvelet-based image fusion has been used to merge a Landsat Enhanced Thematic Mapper Plus Pan and MS image. The proposed method simultaneously provides richer information in the spatial and spectral domains.
ISSN:1545-598X
1558-0571
DOI:10.1109/LGRS.2005.845313