Histogram equalization, image registration, and data fusion for multispectral images

Texture detection using a multispectral approach is naturally superior to a unispectral one because the multispectral process takes more information into account. Details not obvious in one image may be more prominent in others, hence improving the chances of recognition and detection. In this paper we present a new method for preprocessing and eventually fusing a set of multispectral images. Images are preprocessed using histogram equalization, which is found to be ideally suited for this exercise. A wavelet transform technique is used to fuse data from the different multispectral images.