Title :
Fusion of multispectral and panchromatic Satellite images using the curvelet transform
Author :
Choi, Myungjin ; Kim, Rae Young ; Nam, Myeong-Ryong ; Kim, Hong Oh
Author_Institution :
Div. of Appl. Math., Korea Adv. Inst. of Sci. & Technol., Daejeon, South Korea
fDate :
4/1/2005 12:00:00 AM
Abstract :
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.
Keywords :
artificial satellites; geophysical signal processing; geophysical techniques; image resolution; remote sensing; sensor fusion; wavelet transforms; ARSIS; ETM+ image; Landsat Enhanced Thematic Mapper Plus; amelioration de la resolution spatiale par injection de structures; curvelet transform; image fusion; image representation; intensity-hue-saturation; multiresolution analysis; multispectral satellite images; panchromatic satellite images; principal components analysis; remote sensing; spatial resolution; wavelet transform; Data mining; Image fusion; Image resolution; Multiresolution analysis; Principal component analysis; Remote sensing; Satellites; Spatial resolution; Wavelet analysis; Wavelet transforms; Curvelet transform; Landsat Enhanced Thematic Mapper Plus (ETM+) image; image fusion; multiresolution analysis; wavelet transform;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2005.845313