Single-Pixel Based Double Random-Phase Encoding Technique
A new encryption technique based on single-pixel compressive sensing along with a Double Random-Phase encoding (DRPE) is proposed. As compared with the conventional way of image compression where the image information is firstly capture and then compress,
- PDF / 533,263 Bytes
- 12 Pages / 439.37 x 666.142 pts Page_size
- 70 Downloads / 206 Views
Abstract A new encryption technique based on single-pixel compressive sensing along with a Double Random-Phase encoding (DRPE) is proposed. As compared with the conventional way of image compression where the image information is firstly capture and then compress, the single-pixel compressive sensing collects only a few large coefficients of the data information and throws out the remaining which gives scrambled effect on the image. Further, to enhance the complexity of the image data, the double random phase encoding along with a fractional Fourier transform is implemented to re-encrypt it. The single-pixel based compressive sensing, DRPE and fractional Fourier transform act as a secret keys. At the receiver end, the original image data is reconstructed by applying the inverse of double random phase process and an l1 -minimization approach. The peak-to-peak signal-to-noise ratio and the minimum number of compressive sensing measurements to reconstruct the image are used to analyze the quality of the decryption image. The numerical results demonstrate the system to be highly complex, robust and secure.
Keywords Single-pixel Compressed sensing Double Random-Phase encoding Fractional fourier transform Key l1-norm
1 Introduction Several encryption techniques have been applied to secure the data information from attackers [1–3]. A well-known Double Random-Phase encoding (DRPE) proves to be more secure and robust encryption technique [4, 5]. In DRPE, the image is scrambled by two independent phase functions with a Fourier transform N. Rawat (&) School of Mechatronics, Gwangju Institute of Science and Technology, Gwangju 500-712, South Korea e-mail: [email protected] © Springer Science+Business Media Singapore 2016 M. Senthilkumar et al. (eds.), Computational Intelligence, Cyber Security and Computational Models, Advances in Intelligent Systems and Computing 412, DOI 10.1007/978-981-10-0251-9_6
43
44
N. Rawat
(FT). However, more complex algorithms are used such as jigsaw transform [6], Henon chaotic [7], and Arnold transform [8] for pixel scrambling in DRPE as well. These methods enhance the security system of the data by scrambling the content which can be unlocked only by the right decrypted key. The fractional Fourier transform (FRT) is introduced for further improvements in the DRPE approach [9, 10]. FRT provides an extra degree of freedom and enlarges the key space resulting in higher security of data as compared to the FT approach [5]. In encryption, data compression plays an important role and have applied in various encryption based methods [11, 12]; although the encryption scheme cannot achieve perfect compression with high security, it is still significant owing to the high computational complexity of cracking. Compressive sensing (CS) is a new sampling paradigm which extracts only few essential features and throws out the remaining from an image [13]. CS states that the image contains many non-zero coefficients when transformed into an appropriate basis and is possible to measure a sparsely
Data Loading...
