Abstract
Image blurring is a major source of image degradations that leads to loss of details. Detecting blurring region of a photo and evaluating the degree of blurring are crucial for image quality assessment. It’s more complicated for portraiture when the blurring sometimes is deliberate by photographer for visual effects. Aiming at evaluating the blurring metric of snapshot or amateur photos with faces, the paper proposed a simple and effective no-reference method of evaluating image blurring. The key idea is taking into account the artistic purpose on portraiture. The proposed method is based on the concept of Cumulative Probability of Blur Detection and pooling strategy. After computing the burring metric of pixels, the final value of global blurring evaluation is obtained with the pooling strategy according to the characteristic of human skin. Experimental results on public databases and photos collected from Internet show the proposed method can significantly improve the accuracy of objective blurring evaluation metric that have stronger correlation with subjective human assessment.
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Li, Y., Lin, Y. (2020). Evaluating Image Blurring for Photographic Portraiture. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1075. Springer, Cham. https://doi.org/10.1007/978-3-030-32591-6_58
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DOI: https://doi.org/10.1007/978-3-030-32591-6_58
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