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Median Filtering Forensics Scheme for Color Images Based on Quaternion Magnitude-Phase CNN
1 Nanjing University of Information Science & Technology, School of Computer and Software, Nanjing, 210044, China
* Corresponding Author: Jinwei Wang. Email: .
Computers, Materials & Continua 2020, 62(1), 99-112. https://doi.org/10.32604/cmc.2020.04373
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In the paper, a convolutional neural network based on quaternion transformation is proposed to detect median filtering for color images. Compared with conventional convolutional neural network, color images can be processed in a holistic manner in the proposed scheme, which makes full use of the correlation between RGB channels. And due to the use of convolutional neural network, it can effectively avoid the one-sidedness of artificial features. Experimental results have shown the scheme’s improvement over the state-of-the-art scheme on the accuracy of color image median filtering detection.Keywords
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APA Style
Wang, J., Zhang, Y. (2020). Median filtering forensics scheme for color images based on quaternion magnitude-phase CNN. Computers, Materials & Continua, 62(1), 99-112. https://doi.org/10.32604/cmc.2020.04373
Vancouver Style
Wang J, Zhang Y. Median filtering forensics scheme for color images based on quaternion magnitude-phase CNN. Comput Mater Contin. 2020;62(1):99-112 https://doi.org/10.32604/cmc.2020.04373
IEEE Style
J. Wang and Y. Zhang, “Median Filtering Forensics Scheme for Color Images Based on Quaternion Magnitude-Phase CNN,” Comput. Mater. Contin., vol. 62, no. 1, pp. 99-112, 2020. https://doi.org/10.32604/cmc.2020.04373
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Copyright © 2020 The Author(s). Published by Tech Science Press.This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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