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Article type: Research Article
Authors: Xiao, Hong | Li, Panchi*
Affiliations: School of Computer and Information Technology, Northeast Petroleum University, Daqing, Heilongjiang 163318, China
Correspondence: [*] Corresponding author: Panchi Li, School of Computer and Information Technology, Northeast Petroleum University, Daqing, Heilongjiang 163318, China. E-mail: [email protected].
Abstract: Digital steganography is the art and science of hiding information in covert channels, so as to conceal the information and prevent the detection of hidden messages. On the classic computer, the principle and method of digital steganography has been widely and deeply studied, and has been initially extended to the field of quantum computing. Quantum image steganography is a relatively active branch of quantum image processing, and the main strategy currently used is to modify the LSB of the cover image pixels. For the existing LSB-based quantum image steganography schemes, the embedding capacity is no more than 3 bits per pixel. Therefore, it is meaningful to study how to improve the embedding capacity of quantum image steganography. This work presents a novel steganography using reflected Gray code for color quantum images, and the embedding capacity of this scheme is up to 6 bits per pixel. In proposed scheme, the secret qubit sequence is considered as a sequence of 6-bit segments. For 6 bits in each segment, the first 3 bits are embedded into the second LSB of RGB channels of the cover image, and the remaining 3 bits are embedded into the LSB of RGB channels of the cover image using reflected-Gray code to determine the embedded bit from secret information. Following the transforming rule, the LSBs of stego-image are not always same as the secret bits and the differences are up to almost 50%. Experimental results confirm that the proposed scheme shows good performance and outperforms the previous ones currently found in the literature in terms of embedding capacity.
Keywords: Quantum image processing, quantum image steganography, gray code, least-significant-bit, embedding capacity
DOI: 10.3233/IDT-190034
Journal: Intelligent Decision Technologies, vol. 14, no. 3, pp. 291-312, 2020
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