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Multilevel Color Transfer on Images for Providing an Artistic Sight of the World | IEEE Journals & Magazine | IEEE Xplore

Multilevel Color Transfer on Images for Providing an Artistic Sight of the World


Processing blocks in the framework for multilevel color transfer on images. The color palette of a recognized artwork of the Fauve movement is mapped to the input image, ...

Abstract:

This paper represents a twofold approach. On the one hand, we introduce a simple method that encompasses an ensemble of image processing algorithms with a multilevel colo...Show More

Abstract:

This paper represents a twofold approach. On the one hand, we introduce a simple method that encompasses an ensemble of image processing algorithms with a multilevel color transfer approach at its core. On the other hand, the method is applied for providing an artistic look to standard images. The approach proposes a multilevel color transfer in a chromatic channel of the CIELAB color space. Once converted from red, green and blue, a specific channel on both images, input and target (reference), is thresholded in a number of levels. Later, the color transfer is performed between regions from corresponding levels using a classical color transfer method. In the application phase, the color palette of a recognized artwork of the Fauve movement is mapped to the input image, emulating the sight of the artist, characterized by the use of vivid colors. Filtering techniques are applied to the outcome, in order to emulate the basic brushstrokes of the artist. Experimental results are shown, visualizing and comparing the input images with the outcomes.
Processing blocks in the framework for multilevel color transfer on images. The color palette of a recognized artwork of the Fauve movement is mapped to the input image, ...
Published in: IEEE Access ( Volume: 5)
Page(s): 15390 - 15399
Date of Publication: 26 July 2017
Electronic ISSN: 2169-3536

Funding Agency:

Citations are not available for this document.

Cites in Papers - |

Cites in Papers - IEEE (2)

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1.
Jyoti Ranjan Labh, R.K. Dwivedi, "Extensive Study on Color and Light Translation of 2D Images using Machine Learning Approaches", 2021 10th International Conference on System Modeling & Advancement in Research Trends (SMART), pp.290-294, 2021.
2.
Shiguang Liu, Min Pei, "Texture-Aware Emotional Color Transfer Between Images", IEEE Access, vol.6, pp.31375-31386, 2018.

Cites in Papers - Other Publishers (6)

1.
Xianshen Zhu , Enliang Hu , " A local color transfer method based on optimal transmission ", Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023) , pp. 101 , 2023 .
2.
Haiwei Chen, "The main color structure setting of Chinese oil painting based on content analysis method", Applied Mathematics and Nonlinear Sciences, vol.0, no.0, 2023.
3.
V Umarani, M Dimpusowjanya, Dodla Poojitha, Gurijala Sai Sriya, "Application access for chromatic color detection", Journal of Physics: Conference Series, vol.2484, no.1, pp.012049, 2023.
4.
Hsien-Chu Wu, Yu-Chi Liu, Yen-Yu Chen, Yu-Yen Weng, "Adaptive Multilevel Coloring and Significant Texture Selecting for Automatic Deep Learning Image Transfer", Electronics, vol.11, no.22, pp.3750, 2022.
5.
Bin Xie, Xian Li, Changqing Liao, Zihao Ding, "Optimal L_{2}
Color Transfer Based on Adaptive Morphological Reconstrution", Exploration of Novel Intelligent Optimization Algorithms, vol.1590, pp.353, 2022.
6.
Yuzhuo Wang, Yanlin Geng, "Arbitrary Style Transfer with Adaptive Channel Network", MultiMedia Modeling, vol.13141, pp.481, 2022.

References

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