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Contrast Retention De-coloring Based on Cosine Similarity

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Exploration of Novel Intelligent Optimization Algorithms (ISICA 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1590))

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Abstract

Image grayscale is to downscale a 3-dimensional color image into a 1-dimensional grayscale image. Due to the act of downscaling, the information of a 3-dimensional matrix is represented by a 1-dimensional matrix, and there will inevitably be information loss, which makes it very important to maintain the detail contrast information of the original color image to the maximum extent. In this regard, this paper proposes a two-way contrast retention model and algorithm based on cosine similarity. This model consists of two local contrast retention sub-models based on cosine similarity, and the two sub-models achieve complementary functions, which can play a contrast retention dephasing effect on the regions with large contrast and regions with small contrast in the original color image respectively, so that the total model can play a two-way contrast retention effect. In addition, the model is solved using a parameter discrete search strategy to improve the real-time performance of the algorithm.

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Acknowledgement

This work is supported by Natural Science Foundation of Jiangxi Province of China with the Grant No. 20192BAB207036. And partially supported by 2021 Jiangxi University of Science and Technology University-level postgraduate innovation special funds with the Grant No. XY2021-S095.

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Authors and Affiliations

  1. College of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, 341000, Jiangxi, China

    Bin Xie, Zihao Ding, Changqing Liao & Xian Li

  2. College of Electronics and Information Engineering, Shenzhen University, Shenzhen, 523808, Guangdong, China

    Bin Xie

Authors
  1. Bin Xie
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  2. Zihao Ding
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  3. Changqing Liao
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  4. Xian Li
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Corresponding author

Correspondence to Zihao Ding .

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Editors and Affiliations

  1. South China Agricultural University, Guangzhou, China

    Kangshun Li

  2. The University of Aizu, Aizu-Wakamatsu, Japan

    Yong Liu

  3. South China Agricultural University, Guangzhou, China

    Wenxiang Wang

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Xie, B., Ding, Z., Liao, C., Li, X. (2022). Contrast Retention De-coloring Based on Cosine Similarity. In: Li, K., Liu, Y., Wang, W. (eds) Exploration of Novel Intelligent Optimization Algorithms. ISICA 2021. Communications in Computer and Information Science, vol 1590. Springer, Singapore. https://doi.org/10.1007/978-981-19-4109-2_15

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  • DOI: https://doi.org/10.1007/978-981-19-4109-2_15

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-4108-5

  • Online ISBN: 978-981-19-4109-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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