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Multi-focus image fusion by local optimization over sliding windows

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Abstract

This article presents a technique to solve the problem of multi-focus image fusion. This technique is based on the maximization of a linear function with spatial coherence constraints. The final fused image is computed as the sum of the source images using a segmentation map. We can compute the segmentation map using the Simplex method, where the objective function includes one variable associated with each pixel. The Simplex method requires a huge amount of memory resources to produce it. We present an algorithm called CPW-S, which uses some strategies to solve the problem in a context with fewer variables; images are split into regions, thus reducing the computational effort. We present results for two pairs of synthetic images in order to quantify the results, obtaining more than \(98\%\) of pixel accuracy for the segmentation map. We also present results for several pairs of real images (widely used in the literature) and a triad of multi-focus images. The resulting fused images are qualitatively good for all the real images included in the experiments.

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Authors and Affiliations

  1. División de Estudios de Posgrado., Facultad de Ingeniería Eléctrica, Santiago Tapia 403. Col. Centro. C.P 58000., 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, Felix Calderon or Juan Flores.

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Garnica-Carrillo, A., Calderon, F. & Flores, J. Multi-focus image fusion by local optimization over sliding windows. SIViP 12, 869–876 (2018). https://doi.org/10.1007/s11760-017-1229-x

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  • DOI: https://doi.org/10.1007/s11760-017-1229-x

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