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An adaptive enhancement algorithm based on visual saliency for low illumination images

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Abstract

In order to improve the brightness and contrast of low illumination color images and avoid over enhancement, an adaptive image enhancement algorithm based on visual saliency is proposed. Firstly, the original low illumination image is transformed from Red Green Blue (RGB) color space to Hue Saturation Intensity (HSI) color space. Secondly, the bilateral gamma adjustment (BIGA) function combined with the cuckoo search algorithm is used for adaptively increasing the overall brightness of image. In addition, the brightness preserving Bi-histogram construction based on visual salience algorithm (BBHCVS) is proposed to respectively conserve the brightness and improve the contrast of low illuminance color images. Finally, the processed HSI color space is transformed into RGB color space to get the enhanced image. Experimental results demonstrate that the proposed BBHCVS algorithm can effectively enhance the visual salient areas of human perception, and also significantly improve the contrast and brightness of image compared with other well-known and state-of-the-art methods.

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Acknowledgements

This research is financially supported by National Natural Science Foundation of China under Grant 61672470, and The key scientific research projects of universities in Henan province under Grant 20A520004, and the Youth core teacher training program of universities in Henan province under Grant 2019GGJS138.

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Correspondence to Yongsheng Shi.

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Qian, S., Shi, Y., Wu, H. et al. An adaptive enhancement algorithm based on visual saliency for low illumination images. Appl Intell 52, 1770–1792 (2022). https://doi.org/10.1007/s10489-021-02466-4

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