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An efficient image integration algorithm for night mode vision applications

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Abstract

The night mode visible images are often fused with infrared images for increased visual perception and contextual enhancement as the later is equipped with the complimentary information which is otherwise missing due to night mode image acquisition. This technology finds extensive application in the field of armed forces and surveillance. The night mode visible images, due to under-exposure and poor atmospheric conditions are prone to noise and artefacts which leads deterred level of information analysis and extraction. This article not only provides higher visual perception of the individual source images but also proposes an efficient fusion algorithm for visible and infrared images in night mode which is able to generate high quality results with increased focus on the objects of interest competitive with the state-of-the-art methods.

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Authors and Affiliations

  1. Department of Electronics and Communications, Panjab University (UIET), Chandigarh, India

    Ayush Dogra, Bhawna Goyal & Sunil Agrawal

  2. Department of Statistics, Beirut Arab University, Beirut, Lebanon

    Seifedine Kadry

Authors
  1. Ayush Dogra
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  2. Seifedine Kadry
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  3. Bhawna Goyal
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  4. Sunil Agrawal
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Corresponding author

Correspondence to Ayush Dogra.

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Appendix

Appendix

Fig. 6
figure 6

(a) CSR fusion result, (b) ROLP based fusion, (c) SDMF fusion method, (d) M-SVD fusion rule, (e) Two-scale decomposition image fusion method, (f) Guided Filtering, (g) Wavelet based fusion rule, (h) Gradient transfer fusion rule, (i) proposed method

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Table 3 Objective evaluation
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In the results given above, the proposed algorithm is performing subjectively at par with CSR method. But in the results given in Fig. 5, our method performs the best. So it can be concluded that performance of the given algorithm remains consistent with the change in the data set.

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Dogra, A., Kadry, S., Goyal, B. et al. An efficient image integration algorithm for night mode vision applications. Multimed Tools Appl 79, 10995–11012 (2020). https://doi.org/10.1007/s11042-018-6631-z

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  • DOI: https://doi.org/10.1007/s11042-018-6631-z

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