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Incorporating human attention shifting features for enhanced local dimming performance

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Abstract

This paper analyzes the saliency indicators representing human visual attention and proposes a weighted mean square deviation local dimming method based on an image saliency ranking model. It references the saliency ranking model for instance segmentation and saliency ranking, determining the saliency levels of different salient objects in the image, which reflect the importance of different regions. Then, it assigns weights to different regions in the image based on their saliency levels, with regions having higher weights being considered more critical in the image. During dimming, details of critical regions are preserved while the image quality of low attention areas is appropriately reduced, thereby enhancing the subjective visual effects of the image and lowering the power consumption of liquid crystal displays. Specifically, this paper determines the importance of different regions in the image based on saliency order and selects appropriate methods to weight the allowable saturation error in mean square error calculation, ensuring that the optimized saturation error is within the human perceptual range, thereby determining the final backlight values for each region. Simulation results indicate that, compared to common local dimming algorithms and saliency-based global dimming algorithms, an optimal balance is achieved when considering image quality, power consumption, and general applicability across various scenarios.

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Data availability

No data were used to support this study. The dataset and source code are released publicly available on https://doi.org/10.5281/zenodo.10979631

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Acknowledgements

This work is supported by the University Synergy Innovation Program of Anhui Province (Grant No. GXXT-2023-006, GXXT-2023-007, and GXXT-2023-040) and the Major Science and Technology Project of Anhui Province (Grant No. 2021e03020007).

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Authors and Affiliations

  1. Anhui Province Key Laboratory of Measuring Theory and Precision Instrument, School of Instrument Science and Optoelectronic Engineering, Hefei University of Technology, Hefei, 230009, P. R. China

    Xianhui Nie, Yong Fang, Xin Liu, Hao Li, Zi Wang & Longzhen Qiu

  2. Academy of Photoelectric Technology, Anhui Industrial Innovation Research Institute of Advanced Optoelectronic Materials and Systems, Hefei University of Technology, Hefei, 230009, China

    Xianhui Nie, Yong Fang, Xin Liu, Hao Li, Zi Wang & Longzhen Qiu

Authors
  1. Xianhui Nie
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  2. Yong Fang
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  3. Xin Liu
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  4. Hao Li
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  5. Zi Wang
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  6. Longzhen Qiu
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Contributions

L. Q. and Y. F. proposed the topic of the article. X. N. wrote the main manuscript text. All authors reviewed the manuscript.

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Correspondence to Yong Fang or Longzhen Qiu.

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Communicated by Bing-kun Bao.

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Nie, X., Fang, Y., Liu, X. et al. Incorporating human attention shifting features for enhanced local dimming performance. Multimedia Systems 31, 163 (2025). https://doi.org/10.1007/s00530-025-01705-9

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