Color space and wavelet transform for merging multispectral and panchromatic SPOT images

We propose in this paper the joint use of the color space and wavelet transform to improve the spatial resolution of multispectral images. The principle consists in transforming the Red Green Blue (RGB) image components into IHS independent components. The I component is merged with the P image in the wavelet domain via an appropriate model and an IHS reverse transformation is then performed to produce new high resolution multispectral images. For this purpose, the redundant wavelet transform may be used since it ensures that significant details coming from P are well injected in the I component. Another advantage of this approach lies in rejecting the noise present in the two components. The merging I and P considered here is based on the local detail mean matching that allows to adjust the high resolution details of the P image with the low resolution of the I component To evaluate the results of our merging method two criteria are used: correlation coefficient and index deviation.