Fusing images with multiple focuses using support vector machines

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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 the objects in the scene. One approach to address this problem is by performing image fusion, i.e., several pictures with different focus points are combined to a single image. This paper proposes a multifocus image fusion method based on the discrete wavelet frame transform and support vector machines. Experimental results show that the proposed method outperforms the conventional approach based on the discrete wavelet transform and maximum selection rule, particularly when there is slight camera/object movement or mis-registration of the source images. © Springer-Verlag Berlin Heidelberg 2002.

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APA

Li, S., Kwok, J. T., & Wang, Y. (2002). Fusing images with multiple focuses using support vector machines. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2415 LNCS, pp. 1287–1292). Springer Verlag. https://doi.org/10.1007/3-540-46084-5_208

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