Image Hiding Method Based on Two-Channel Deep Convolutional Neural Network

DUAN Xintao; WANG Wenxin; LI Lei; SHAO Zhiqiang; WANG Xianfang; QIN Chuan

doi:10.11999/JEIT210280

Volume 44 Issue 5

May 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(5): 1782-1791

DUAN Xintao, WANG Wenxin, LI Lei, SHAO Zhiqiang, WANG Xianfang, QIN Chuan. Image Hiding Method Based on Two-Channel Deep Convolutional Neural Network[J]. Journal of Electronics & Information Technology, 2022, 44(5): 1782-1791. doi: 10.11999/JEIT210280

Citation:

DUAN Xintao, WANG Wenxin, LI Lei, SHAO Zhiqiang, WANG Xianfang, QIN Chuan. Image Hiding Method Based on Two-Channel Deep Convolutional Neural Network[J]. Journal of Electronics & Information Technology, 2022, 44(5): 1782-1791. doi: 10.11999/JEIT210280

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Image Hiding Method Based on Two-Channel Deep Convolutional Neural Network

doi: 10.11999/JEIT210280

1.
College of Computer and Information Engineering, Henan Normal University, Xinxiang 453007, China
2.
College of Computer Science and Technology, Henan Institute of Technology, Xinxiang 453003, China
3.
School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China

Funds: The National Natural Science Foundation of China (U1904123, 61672354, 62072157), The Key Laboratory Foundation of Artificial Intelligence and Personalized Learning in Education of Henan Province

Received Date: 2021-04-06
Accepted Date: 2021-09-13
Rev Recd Date: 2021-09-13

Available Online: 2021-12-22

Publish Date: 2022-05-25

Abstract

Abstract

The existing image information hiding methods based on Deep Convolutional Neural Networks (DCNN) have the problems of poor image visual quality and low hiding capacity. Addressing such issues, an image hiding method based on a two-channel deep convolutional neural network is proposed. First, different from the previous hiding framework, the hiding method proposed in this paper includes one hiding network and two revealing networks with the same structure, and two full-size secret images can be effectively hidden and revealed at the same time is realized. Then, to improve the visual quality of the image, an improved pyramid pooling module and a preprocessing module are added to the hiding and revealing network. The test results on multiple data sets show that the proposed method has a significant improvement in visual quality compared with existing image information hiding methods. The Peak Signal-to-Noise Ratio (PSNR) and Structural SIMilarity (SSIM) values are increased by 3.75 dB and 3.61 % respectively, a relative capacity of 2 and good generalization ability are achieved.
- Image information hiding,
- Deep Convolutional Neural Networks (DCNN),
- Pyramid pooling,
- Preprocessing

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References(23)

References

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