caa a22 4500 605447144 CHVBK 20210128100130.0 cr unu---uuuuu 210128e20151101xx s 000 0 eng 10.1007/s11042-014-2076-1 doi (NATIONALLICENCE)springer-10.1007/s11042-014-2076-1 Image steganography based on subsampling and compressive sensing [Elektronische Daten] [Jeng-Shyang Pan, Wei Li, Chun-Sheng Yang, Li-Jun Yan] A new image steganography algorithm combining compressive sensing with subsampling is proposed, which can hide secret message into an innovative embedding domain. Considering that natural image tends to be compressible in a transform domain, the characteristics of compressive sensing (CS), dimensional reduction and random projection, are utilized to insert secret message into the compressive sensing transform domain of the sparse image and the measurement matrix which is generated by using a secret key is shared between sender and receiver. Then, stego-image is reconstructed approximately via Total Variation (TV) minimization algorithm. Through adopting different transform coefficients in sub-images gained by subsampling, high perceived quality of the stego-image can be guaranteed. Bit Correction Rate (BCR) between original secret message and extracted message are used to calculate the accuracy of this method. Numerical experiments show that this steganography algorithm has provided a novel data embedding domain and high security of information. Springer Science+Business Media New York, 2014 Steganography nationallicence Compressive Sensing(CS) nationallicence Subsampling nationallicence Total variation nationallicence Pan Jeng-Shyang IIIRC, School of Computer Science & Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China aut Li Wei IIIRC, School of Computer Science & Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China aut Yang Chun-Sheng IIIRC, School of Computer Science & Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China aut Yan Li-Jun IIIRC, School of Computer Science & Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China aut Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/21(2015-11-01), 9191-9205 1380-7501 74:21<9191 2015 74 11042 https://doi.org/10.1007/s11042-014-2076-1 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11042-014-2076-1 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Pan Jeng-Shyang IIIRC, School of Computer Science & Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China aut NATIONALLICENCE 700 1- Li Wei IIIRC, School of Computer Science & Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China aut NATIONALLICENCE 700 1- Yang Chun-Sheng IIIRC, School of Computer Science & Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China aut NATIONALLICENCE 700 1- Yan Li-Jun IIIRC, School of Computer Science & Technology, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China aut NATIONALLICENCE 773 0- Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/21(2015-11-01), 9191-9205 1380-7501 74:21<9191 2015 74 11042