Multifocus image fusion using spatial features and support vector machine

Authors:
Shutao Li;Yaonan Wang
Affiliations:
College of Electrical and Information Engineering, Hunan University, Changsha, Hunan and National Laboratory on Machine Perception, Peking University, Beijing, China;College of Electrical and Information Engineering, Hunan University, Changsha, Hunan, China
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
Year:
2005

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Abstract

This paper describes an application of support vector machine to pixel-level multifocus image fusion problem based on the use of spatial features of image blocks. The algorithm first decomposes the source images into blocks. Given two of these blocks (one from each source image), a SVM is trained to determine which one is clearer. Fusion then proceeds by selecting the clearer block in constructing the final image. Experimental results show that the proposed method outperforms the discrete wavelet transform based approach, particularly when there is movement in the objects or misegistration of the source images.