An adaptive image fusion algorithm based on ICA

Image fusion can be viewed as a process that incorporates essential information from different modality sensors into a composite image. The use of based trained Independent Component Analysis (ICA) for image fusion has been high-lighted recently. Common fusion rules can be used in the ICA fusion framework with promising results, but has the shortcoming of the same fuse rule for the whole image. In this paper, we propose an adaptive algorithm which based on the ICA fusion framework that maximizes the sparsity of the fusion image in the frame domain. The experiment results show its excellent performance in image fusion.