  Image registration is a fundamental issue in multispectral image processing.
In filter wheel based multispectral imaging systems, the non-coplanar placement
of the filters always causes the misalignment of multiple channel images. The
selective characteristic of spectral response in multispectral imaging raises
two challenges to image registration. First, the intensity levels of a local
region may be different in individual channel images. Second, the local
intensity may vary rapidly in some channel images while keeps stationary in
others. Conventional multimodal measures, such as mutual information,
correlation coefficient, and correlation ratio, can register images with
different regional intensity levels, but will fail in the circumstance of
severe local intensity variation. In this paper, a new measure, namely
normalized total gradient (NTG), is proposed for multispectral image
registration. The NTG is applied on the difference between two channel images.
This measure is based on the key assumption (observation) that the gradient of
difference image between two aligned channel images is sparser than that
between two misaligned ones. A registration framework, which incorporates image
pyramid and global/local optimization, is further introduced for rigid
transform. Experimental results validate that the proposed method is effective
for multispectral image registration and performs better than conventional
methods.
