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Multifocus color image sequence fusion based on mean shift segmentation

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Abstract

This paper presents a region-based technique for fusion of a multifocus color image sequence in the LUV color space. First, mean shift segmentation was applied on the weighted average image of the image sequence to obtain the fusion reference areas. Second, for each segmented area, the well-known modified Laplacian (LAP2) was used as a focus measure to select the clearest parts within the image sequence and then a final image focused with all parts can be generated. Mutual information, QAB/F metric, entropy, standard deviation, image sharpness metric, image contrast metric, average gradient, and spatial frequency were adopted to assess the quality of the fused image. Experiments carried out using standard image sequences from HeliconSoft demonstrated that the results obtained through our technique offer good performance. The proposed technique can be used to extend the depth of field (DOF) of a camera system effectively.

© 2015 Optical Society of America

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Corrections

19 October 2015: Corrections were made to the funding section.


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