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An Efficient Anti-ghost Multiple Exposure Fusion with Detail Preserving

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Advances in Intelligent Automation and Soft Computing (IASC 2021)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 80))

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Abstract

In order to solve the problem of detail-preserving and ghost-elimination in multi-exposure image fusion, this paper uses an improved Butterworth low-pass filter curve to determine the absolute exposure weight of each pixel in the input image, calculates the relative exposure weight based on the reference image according to the gradient direction information of the pixel, and proposes a moving-object correction method to detect and eliminate the pixels which change suddenly in the exposure sequence. Experimental results show that this algorithm can successfully generate fusion results with good performance, and can retain most of the details and texture information of the sequence while removing ghosts. In addition to the traditional image processing field, the algorithm can also be applied to mobile robot intelligent inspection and defect detection and other engineering fields which rely on image processing.

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Acknowledgements

This work is supported by science and technology project of China Southern Power Grid Corporation (080007kk52180005).

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Authors and Affiliations

  1. Guangzhou Power Supply Bureau of Guangdong Power Grid Co., Ltd., Guangzhou, 510620, Guangdong, China

    Guokai Liang, Jingru He, Linhuan Luo, Jian Liu & Guokun Xiong

Authors
  1. Guokai Liang
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  2. Jingru He
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  3. Linhuan Luo
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  4. Jian Liu
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  5. Guokun Xiong
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Corresponding author

Correspondence to Guokun Xiong .

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Editors and Affiliations

  1. Electronics and Computer Engineering Technology, Indiana State University, Terre Haute, IN, USA

    Xiaolong Li

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Liang, G., He, J., Luo, L., Liu, J., Xiong, G. (2022). An Efficient Anti-ghost Multiple Exposure Fusion with Detail Preserving. In: Li, X. (eds) Advances in Intelligent Automation and Soft Computing. IASC 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 80. Springer, Cham. https://doi.org/10.1007/978-3-030-81007-8_84

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