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Multi-focus image fusion for multiple images using adaptable size windows and parallel programming

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Abstract

The multi-focus image fusion with adaptable windows (MF-AW) algorithm for multiple images improves the results of the linear combination of images with variable windows (CLI-VV—from its Spanish acronym) algorithm, using a unique decision map and applying parallel programming. Other algorithms use the same window size throughout the image to produce a decision map; furthermore, a different decision map is produced for each pair of images. MF-AW determines the largest possible window size delimited by the edges of the decision map, which are improved using an iterative process. The execution time is improved using integral images, binary search, and parallel programming; as a result, the fused image is obtained in tenths of a second. Quantitative and qualitative measures indicate that the results obtained with this algorithm outperform the state of the art in terms of both accuracy and execution time.

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Authors and Affiliations

  1. DEP-FIE, Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán, Mexico

    Adan Garnica-Carrillo, Felix Calderon & Juan Flores

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  1. Adan Garnica-Carrillo
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  2. Felix Calderon
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  3. Juan Flores
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Correspondence to Adan Garnica-Carrillo.

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Garnica-Carrillo, A., Calderon, F. & Flores, J. Multi-focus image fusion for multiple images using adaptable size windows and parallel programming. SIViP 14, 1293–1300 (2020). https://doi.org/10.1007/s11760-020-01668-6

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  • DOI: https://doi.org/10.1007/s11760-020-01668-6

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