Multispectral image fusion based on diffusion morphology for enhanced vision applications

Existing image fusion methods based on morphological image analysis, that expresses the geometrical idea of image shape as a label image, are quite sensitive to the quality of image segmentation and, therefore, not sufficiently robust to noise and high frequency distortions. On the other hand, there are a number of methods in the field of dimensionality reduction and data comparison that give possibility of avoiding an image segmentation step by using diffusion maps techniques. The paper proposes a new approach for multispectral image fusion based on the combination of morphological image analysis and diffusion maps theory (i.e. Diffusion Morphology). A new image fusion algorithm is described that uses a matched diffusion filtering procedure instead of morphological projection. The algorithm is implemented for a three channels Enhanced Vision System prototype. The comparative results of image fusion are shown on real images acquired in flight experiments.