Abstract
Low light or poor shooting angle and other issues often make the camera to take night time images and affect the naked-eye observation or computer identification, so it is important to enhance the lightness of night time image. Although the existing non-linear luminance enhancement method can improve the brightness of the low light area, the excessive promotion led to high light area distortion. Based on the existing image luminance processing algorithm, we proposed an adaptive night time image improving method in the basis of nonlinear brightness enhancement model is proposed to process the segmentations of image brightness by using the logarithmic function. The segmentation threshold is determined by the Otsu, and the adjustment factor of the backlight region in the transfer function is calculated from the area ratio of the backlight area. The conclusion comes from the simulation. The method involves improving the image quality and ensuring that the entire picture is natural without distortion. In the meanwhile, the processing speed is not much slower compared with the existing processing algorithms.
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Acknowledgments
This work was partially supported by the NSF project of Shandong province in China with granted No. ZR2014FM023, and Research and Innovation Fund project of Harbin Institute of Technology with granted No. HIT.NSRIF.2016108.
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Zhang, Y., Wang, C., Wang, X., Wang, J., Man, L. (2018). Night Time Image Enhancement by Improved Nonlinear Model. In: Gu, X., Liu, G., Li, B. (eds) Machine Learning and Intelligent Communications. MLICOM 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 227. Springer, Cham. https://doi.org/10.1007/978-3-319-73447-7_34
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DOI: https://doi.org/10.1007/978-3-319-73447-7_34
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