Multifocus image fusion using artificial neural networks

Authors:
Shutao Li;James T. Kwok;Yaonan Wang
Affiliations:
College of Electrical and Information Engineering, Hunan University, Changsha 410082, People's Republic of China and Department of Computer Science, Hong Kong University of Science and Technology, ...;Department of Computer Science, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong;College of Electrical and Information Engineering, Hunan University, Changsha 410082, People's Republic of China
Venue:
Pattern Recognition Letters
Year:
2002

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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 a movement in the objects or misregistration of the source images.