Optimal Contrast Correction for ICA-Based Fusion of Multimodal Images

Abstract

In this paper, the authors revisit the previously proposed Image Fusion framework, based on self-trained independent component analysis (ICA) bases. In the original framework, equal importance was given to all input images in the reconstruction of the ldquofusedrdquo image's intensity. Even though this assumption is valid for all applications involving sensors of the same modality, it might not be optimal in the case of multiple modality inputs of different intensity range. The authors propose a method for estimating the optimal intensity range (contrast) of the fused image via optimization of an image fusion index. The proposed approach can be employed in a general fusion scenario including multiple sensors.