Multifocus image fusion using artificial neural networks

Shutao Li, James T. Kwok and Yaonan Wang

Abstract: Optical lenses, particularly those with long focal lengths, suffer from the problem of limited depth of field. Consequently, it is often difficult to obtain good focus for all objects in the picture. One possible solution is to take several pictures with different focus points, and then combine them together to form a single image. This paper describes an application of artificial neural networks to this pixel level multifocus image fusion problem based on the use of image blocks. Experimental results show that the proposed method outperforms the discrete wavelet transform based approach, particularly when there is movement in the objects or mis-registration of the source images.

Pattern Recognition Letters, 23(8): 985-997, June 2002.


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