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Fusion of multi-exposure images using recursive and Gaussian filter

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Abstract

This paper proposes a novel technique to create a high-resolution image by combining the bracketed exposure sequence without a priori knowledge of source image. The source image is split into three categories: constant, high varying and low varying feature images. For high and low varying features, pixels with highest information is selected and combined to construct collective high and low varying feature image. Collective constant feature image is constructed from weighted average of constant feature images, where weight is calculated based on information present in original source images. These pre-processed high, low and constant feature images are further combined to produce a final fused image. Objective analysis based quality evaluation parameters show a significant improvement in result produced by proposed method against the state-of-the-art.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Thapar Institute of Engineering and Technology, Patiala, India

    Vishal Chaudhary & Vinay Kumar

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  1. Vishal Chaudhary
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  2. Vinay Kumar
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Correspondence to Vishal Chaudhary.

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Chaudhary, V., Kumar, V. Fusion of multi-exposure images using recursive and Gaussian filter. Multidim Syst Sign Process 31, 157–172 (2020). https://doi.org/10.1007/s11045-019-00655-6

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  • DOI: https://doi.org/10.1007/s11045-019-00655-6

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