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

作者:Shenyi Qian, Yongsheng Shi, Huaiguang Wu, Jinhua Liu, Weiwei Zhang

摘要

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.

论文关键词:Color image enhancement, Low illumination, Cuckoo search, Visual saliency, Bilateral gamma adjustment

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论文官网地址:https://doi.org/10.1007/s10489-021-02466-4