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An Adaptive Low Illumination Color Image Enhancement Method Using Dragonfly Algorithm

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Methods and Applications for Modeling and Simulation of Complex Systems (AsiaSim 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1712))

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Abstract

In order to improve the visual perception of color images under low illumination conditions, an adaptive enhancement method is proposed to enhance the contrast and brightness, enrich the color and avoid over-enhancement. Firstly, the original low illumination image is converted from RGB color space to L*a*b* color space, and a novel gray level transformation function namely piecewise sine function is proposed to improve the brightness of L* channel image. In addition, dragonfly algorithm is utilized to optimize the parameters in piecewise sine function to achieve the best brightness adjustment effect. Then a novel saturation enhancement method is proposed to enrich color information. Subsequently, a fitness function that takes into account both the degree of overall brightness enhancement and the suppression of information loss is applied as the objective function of dragonfly algorithm. Ultimately, the processed L*a*b* color space is transformed back to RGB color space to get the enhanced image. Experimental results verify the effectiveness of the proposed method.

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Authors and Affiliations

  1. Shanghai University, Shanghai, China

    Jiang Liu & Shiwei Ma

Authors
  1. Jiang Liu
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  2. Shiwei Ma
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Corresponding author

Correspondence to Shiwei Ma .

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Editors and Affiliations

  1. Tsinghua University, Bei**g, China

    Wenhui Fan

  2. Beihang University, Bei**g, China

    Lin Zhang

  3. Beihang University, Bei**g, China

    Ni Li

  4. Beihang University, Bei**g, China

    **ao Song

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Liu, J., Ma, S. (2022). An Adaptive Low Illumination Color Image Enhancement Method Using Dragonfly Algorithm. In: Fan, W., Zhang, L., Li, N., Song, X. (eds) Methods and Applications for Modeling and Simulation of Complex Systems. AsiaSim 2022. Communications in Computer and Information Science, vol 1712. Springer, Singapore. https://doi.org/10.1007/978-981-19-9198-1_16

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  • DOI: https://doi.org/10.1007/978-981-19-9198-1_16

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-9197-4

  • Online ISBN: 978-981-19-9198-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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