Abstract
In this paper, a new image mining method is proposed considering the contrast resolution limitation of human vision under scotopic visual environment. First, a valid gray distribution of an image is taken from scotopic vision condition. Second, the gray values of a target image pixels are computed from the original image via Zadeh-X transformation. Third, a no reference image quality assessment function (NR-IQAF) is used to estimate the image after transformation. Experiments demonstrate that this method greatly improves the visual contrast and luminance of the image, so image quality and visual effects have been improved significantly after mining; in addition, the optimal quality image can be obtained by the NR-IQAF.
The project is supported by National Natural Science Foundation of China. Grant No.60975008.
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Tian, F., Lv, X., Cheng, J., Xie, Z. (2011). Scotopic Visual Image Mining Based on NR-IQAF. In: Wu, Y. (eds) Computing and Intelligent Systems. ICCIC 2011. Communications in Computer and Information Science, vol 234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24091-1_38
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DOI: https://doi.org/10.1007/978-3-642-24091-1_38
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