A lossless information embedding algorithm based on data reconstruction

Yi Zhang; Quan Zhou; Xuemin Sun; Lang Huyan; Juanni Liu; Mengyao Liu

doi:10.1117/12.2674503

28 April 2023 A lossless information embedding algorithm based on data reconstruction

Yi Zhang, Quan Zhou, Xuemin Sun, Lang Huyan, Juanni Liu, Mengyao Liu

Proceedings Volume 12626, International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022); 126262U (2023) https://doi.org/10.1117/12.2674503
Event: International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022), 2022, Zhuhai, China

Abstract

At present, the network connection scale in the communication and transmission system is expanding with the increasing traffic, it is not easy to process the data, which is inefficient and difficult to ensure the quality of service. In order to increase the system transmission capacity and make the processing more efficient, a lossless information embedding algorithm based on data reconstruction is proposed, according to the characteristics of large variance and discrete distribution of different image, text, and voice data in the communication transmission system. Combined with the data characteristics of each group, interval mapping is carried out for segmented data, which is reorganized by certain rules to increase the redundancy of this segment and expand the data embedding range. The proposed algorithm realizes the lossless embedding of information and the original carrier data and embedded information are recovered losslessly. Simulation results show that the algorithm expands the redundancy range of segmented data and increases the capacity of information embedding, which is suitable for different data transmission systems.

Citation Download Citation

Yi Zhang, Quan Zhou, Xuemin Sun, Lang Huyan, Juanni Liu, and Mengyao Liu "A lossless information embedding algorithm based on data reconstruction", Proc. SPIE 12626, International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022), 126262U (28 April 2023); https://doi.org/10.1117/12.2674503

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