Abstract
Contrapose the problem that the traditional grayscale image colorization results are not unique, this paper proposes a color conversion method based on luminance and Local Binary Patterns (LBP) texture features, which uses an improved Gaussian Mixture Model (GMM) clustering or image segmentation. The cascading feature matching method performs fast feature matching of sub-blocks after segmentation, which overcomes the low matching accuracy of the global color conversion algorithm, long feature matching processing time, and color conversion errors. The verification results of subjective and objective evaluation experiment shows that the method has obvious advantages.
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References
Teng S (2006) Research on colorization of black and white images [J]
He X, Qiao Y (2014) Study on the color transformation of grayscale images based on Welsh algorithm [J]. Computer application and software 31(12): 268–271
Wang S, Donghui L (2010) Image colorization method based on optimal clustering number and histogram matching [J]. J Comput Appl 30(2):351–353
Iizuka S, Simo-Serra E, Ishikawa H (2016) Let there be color: Joint end-to-end learning of global and local image priors for automatic image colorization with simultaneous classification [J]. ACM Trans Graphics (TOG) 35(4):110
Huang G, Han X, Gong X, et al (2019) Grayscale image colorization algorithm based on image segmentation and region matching [J]. Liquid Crystal Display 34(6): 619–626
Tai YW, Jia J, Tang CK (2005) Local color conversion via probabilistic segmentation by expectation-maximization. In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05). IEEE vol 1, pp 747–754
 Li W, Yang F, Fu A (2012) Research on the evaluation of the effect of gray image coloriation[J]. Shanxi Electron Technol 2012(2):78–80
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This work is funded by Digital Imaging Theory- GK188800299016–054.
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© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Zhang, S., Zhuang, R., Cao, J., Lu, S., Wang, Q. (2021). Study on Colorization Method of Grayscale Image. In: Zhao, P., Ye, Z., Xu, M., Yang, L., Zhang, L., Zhu, R. (eds) Advances in Graphic Communication, Printing and Packaging Technology and Materials. Lecture Notes in Electrical Engineering, vol 754. Springer, Singapore. https://doi.org/10.1007/978-981-16-0503-1_15
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DOI: https://doi.org/10.1007/978-981-16-0503-1_15
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