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Image quality assessment via colour information fluctuation

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Abstract

Image quality is an important metric for measuring multimedia services; thus, analysing image quality accurately has high practicability. The existing image quality assessment (IQA) methods mainly focus on grey information, which underutilize the colour information. In this paper, a new IQA method is proposed to make full use of colour information. The method calculates the colour information fluctuation (CF) around each pixel in different detection directions, and obtain CF maps (CFMs). Meanwhile, the greyscale fluctuations (GFs) are analysed to extract GF maps (GFMs). Based on CFMs and GFMS, the direction information is calculated to form CF direction map (CFD) and GF direction map (GFD). After that, the histogram-based features are extracted from CFMs, GFMs, CFDs and GFDs. Finally, different features are combined to measure quality variations comprehensively. The performance comparisons demonstrate the proposed method is competitive with prevalent methods, and is suitable for both natural image and screen content image.

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Acknowledgements

This paper is supported by the National Natural Science Foundation of China (Grant No. 62101268), the National Natural Science Foundation of China (Grant No. 41971343), the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (Grant No. 20KJB510021), the Natural Science Foundation of Jiangsu Province (Grant No. BK20210696) and the Future Network Scientific Research Fund Project (Grant No. FNSRFP-2021-ZD-24).

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Authors and Affiliations

  1. School of Computer and Electronic Information/School of Artificial Intelligence, Nanjing Normal University, No. 1 Wenyuan Road Qixia District, Nanjing, China

    Xichen Yang & Genlin Ji

  2. School of Artificial Intelligence and Information Technology, Nanjing University of Chinese Medicine, No. 138 Xianlin Road Qixia District, Nanjing, China

    Tianshu Wang

Authors
  1. Xichen Yang
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  2. Tianshu Wang
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  3. Genlin Ji
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Contributions

XY conceived and designed the experiments. XY performed the experiments. XY analysed the data. XY, GJ and TW wrote and reviewed the paper. XY, GJ and TW approved the final version of the paper.

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Correspondence to Xichen Yang.

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Yang, X., Wang, T. & Ji, G. Image quality assessment via colour information fluctuation. SIViP 17, 1161–1171 (2023). https://doi.org/10.1007/s11760-022-02323-y

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