TY - GEN
T1 - An Improved of Joint Reversible Data Hiding Methods in Encrypted Remote Sensing Satellite Images
AU - Nasution, Ali Syahputra
AU - Wibisono, Gunawan
N1 - Funding Information:
The authors would like to thank Universitas Indonesia for funding through PUTI Prosiding Universitas Indonesia (UI), under contract No. NKB-1183/UN2.RST/HKP.05.00/2020.
Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - Data protection security is very necessary when distributing high resolution remote sensing satellite images from LAPAN to users via electronic media. Reversible data hiding and encryption are two very useful methods for protecting privacy and data security. This paper proposes an increase in the method of joint reversible data hiding on remote sensing satellite images based on the algorithm of Zhang’s work, Hong et al.’s work, and Fatema et al.’s work. To evaluate the smoothness of the blocks, a modification of the fluctuation calculation function is presented. The experimental results show that the modified calculation function gives better estimation results. Then, the proposed method gives a lower extracted bit error rate and the visual quality of the image from the proposed method is better than the three references. For example, when the block size is 8 × 8, the extracted-bit error rate (EER) of the SPOT-6 test image of the proposed modified function was 8.40%, which is quite lower than the 14.14% EER of Zhang’s function, 9.62% EER of Hong et al.’s function and 11.87% EER of Fatema’s et al.’s method. Likewise, the quality of SPOT-6 image recovery represented by the peak signal-to-noise ratio (PSNR) of proposed modified function is 50.52 dB, which is slightly higher than the 48.23 dB PSNR of Zhang’s function, 49.93 dB PSNR of Hong et al.’s function and 49.00 dB PSNR of Fatema’s et al.’s function.
AB - Data protection security is very necessary when distributing high resolution remote sensing satellite images from LAPAN to users via electronic media. Reversible data hiding and encryption are two very useful methods for protecting privacy and data security. This paper proposes an increase in the method of joint reversible data hiding on remote sensing satellite images based on the algorithm of Zhang’s work, Hong et al.’s work, and Fatema et al.’s work. To evaluate the smoothness of the blocks, a modification of the fluctuation calculation function is presented. The experimental results show that the modified calculation function gives better estimation results. Then, the proposed method gives a lower extracted bit error rate and the visual quality of the image from the proposed method is better than the three references. For example, when the block size is 8 × 8, the extracted-bit error rate (EER) of the SPOT-6 test image of the proposed modified function was 8.40%, which is quite lower than the 14.14% EER of Zhang’s function, 9.62% EER of Hong et al.’s function and 11.87% EER of Fatema’s et al.’s method. Likewise, the quality of SPOT-6 image recovery represented by the peak signal-to-noise ratio (PSNR) of proposed modified function is 50.52 dB, which is slightly higher than the 48.23 dB PSNR of Zhang’s function, 49.93 dB PSNR of Hong et al.’s function and 49.00 dB PSNR of Fatema’s et al.’s function.
KW - EER
KW - Encrypted remote sensing satellite images
KW - Fluctuation function
KW - Joint reversible data hiding
KW - PSNR
UR - http://www.scopus.com/inward/record.url?scp=85097089021&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-63119-2_21
DO - 10.1007/978-3-030-63119-2_21
M3 - Conference contribution
AN - SCOPUS:85097089021
SN - 9783030631185
T3 - Communications in Computer and Information Science
SP - 252
EP - 263
BT - Advances in Computational Collective Intelligence - 12th International Conference, ICCCI 2020, Proceedings
A2 - Hernes, Marcin
A2 - Wojtkiewicz, Krystian
A2 - Szczerbicki, Edward
PB - Springer Science and Business Media Deutschland GmbH
T2 - 12th International Conference on International Conference on Computational Collective Intelligence, ICCCI 2020
Y2 - 30 November 2020 through 3 December 2020
ER -