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Multimodal Registration and Fusion of Industrial CT Data

In this work we present a workflow to register and fuse single scalar data of multimodal imaging techniques. For this purpose the datasets of each modality need to be precisely and robustly registered. In the second step the registered datasets are then combined in a single representation, the fused output dataset. We are using a 3D image registration approach based on mutual information and present two methods for image fusion, one performed in the spatial domain by averaging and one in the transform domain by wavelet analysis. Visualization tools such as magic lenses, difference images and checkerboard visualizations are introduced to interactively explore the registration result as well as the combined images. Furthermore, using color and opacity mapping the users may focus on the exploration of details in the datasets. For evaluation of the performance the proposed workflow is applied and discussed on real world industrial parts made of carbon-fibre-reinforced polymers and wood-plastic composites.