Title :
Fusion of Multispectral and Panchromatic Images Using a Restoration-Based Method
Author :
Li, Zhenhua ; Leung, Henry
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Calgary, Calgary, AB
fDate :
5/1/2009 12:00:00 AM
Abstract :
Many remote-sensing satellites can obtain images in multispectral and panchromatic bands. By fusing low-resolution multispectral and high-resolution panchromatic images, one can obtain high-resolution multispectral images. In this paper, an image fusion algorithm based on image restoration is proposed to combine multispectral and panchromatic images. For remote-sensing satellites, the wavelength of the panchromatic band usually covers the wavelengths of the multispectral bands. This relationship between the two kinds of images is useful for fusion. In our approach, the low-resolution multispectral images are first resampled to the scale of the high-resolution panchromatic image. The relationship between these two kinds of images is then used to restore the resampled multispectral images. That is, the resampled multispectral images are modeled as the noisy blurred versions of the ideal multispectral images, and the high-resolution panchromatic image is modeled as a linear combination of the ideal multispectral images plus the observation noise. The ideal high-resolution multispectral images are then estimated based on the panchromatic and the resampled multispectral images. A closed-form solution of the fused images is derived here. Experiments show that the proposed fusion algorithm works effectively in integrating multispectral and panchromatic images.
Keywords :
geophysical signal processing; geophysical techniques; image fusion; image registration; image restoration; remote sensing; IKONOS data; QuickBird data; image fusion algorithm; image registration; image restoration; low-resolution multispectral image; multispectral band image; noisy blurred version; panchromatic band image; remote sensing satellite; Image fusion; image restoration; multispectral image; panchromatic image; remote sensing;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2008.2005639