Abstract
In view of the problems of poor color classification, poor hierarchy and more artifacts in traditional color transfer methods, this paper proposes an adaptive color transfer method combining morphological segmentation and optimal \(L_{2}\) divergence. Firstly, the adaptive segmentation matrix of the reference image and the content image is obtained by the morphological segmentation algorithm, and the useless regions of the reference image and the content image are filtered out, and the regions with strong color sense are retained. Secondly, by calculating the probability density, the mapping relationship between the probability density function of the reference image and the content image is obtained, and the color transfer is carried out by TPS algorithm. Finally, a large number of experimental results show that the results obtained by the proposed method can better maintain the structural sense of the content image and the color sense of the reference image.
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Acknowledgement
The project has been partially supported by Natural Science Foundation of Jiangxi Province of China (No.: 20192BAB207036).
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Xie, B., Li, X., Liao, C., Ding, Z. (2022). Optimal \(L_{2}\) Color Transfer Based on Adaptive Morphological Reconstrution. In: Li, K., Liu, Y., Wang, W. (eds) Exploration of Novel Intelligent Optimization Algorithms. ISICA 2021. Communications in Computer and Information Science, vol 1590. Springer, Singapore. https://doi.org/10.1007/978-981-19-4109-2_32
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DOI: https://doi.org/10.1007/978-981-19-4109-2_32
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