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A feature-level image fusion method based on segmentation region and neural networks is proposed in this paper. Firstly, the source images are segmented and merged into a set of common regions which are used for guiding the whole fusion process; then selecting the corresponding segmentation regions from the source images respectively and extracting features representing clarity in the two regions; at last the features are fed into a neural networks to judge clear region to reconstruct the final fusion image. The experimental results show that the fusion effect is better.
Date of Conference: 6-8 July 2007