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A critical analysis of the multi-focus image fusion using discrete wavelet transform and computer vision

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Abstract

This paper focused on the in-depth analysis of the multi-focus image fusion processing to enhance image fusion quality. The lack of reliable image information is a challenge to proper object localization. In this paper, I proposed an integrated approach for DWT and computer vision for multi-focus image fusion analysis for the fused image coefficient selection process. I made an in-depth analysis and improvement on the existing algorithms of the wavelet transform and the rules of multi-focus image fusion for object features’ extractions. The wavelet transform uses authentic localization segments, and computer vision improved image fusion processing time to analyze object focus in the high-frequency precision and steps. The process of image fusion using wavelet transformation is the wavelet basis function and wavelet decomposition level in iterative experiments to gain high-quality fused image information. The rules of multi-focus image fusions are the wavelet transformation of the features of the high-frequency coefficients, which enhance the fusion image features reliability on the frequency domain and regional contrast of the object.

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Acknowledgements

I would like to thank the anonymous reviewers for their detailed review, valuable comments, and constructive suggestions. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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  1. Institute of Technology, Bahir Dar University, Poly Main Campus, Agri Building 71, First Floor, Bahir Dar, Ethiopia

    Gebeyehu Belay Gebremeskel

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Gebremeskel, G.B. A critical analysis of the multi-focus image fusion using discrete wavelet transform and computer vision. Soft Comput 26, 5209–5225 (2022). https://doi.org/10.1007/s00500-022-06998-w

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