Abstract

We report a new spectral multiple image fusion analysis based on the discrete cosine transform (DCT) and a specific spectral filtering method. In order to decrease the size of the multiplexed file, we suggest a procedure of compression which is based on an adapted spectral quantization. Each frequency is encoded with an optimized number of bits according its importance and its position in the DC domain. This fusion and compression scheme constitutes a first level of encryption. A supplementary level of encryption is realized by making use of biometric information. We consider several implementations of this analysis by experimenting with sequences of gray scale images. To quantify the performance of our method we calculate the MSE (mean squared error) and the PSNR (peak signal to noise ratio). Our results consistently improve performances compared to the well-known JPEG image compression standard and provide a viable solution for simultaneous compression and encryption of multiple images.

© 2011 OSA

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References

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  1. A. Alfalou and C. Brosseau, “Optical image compression and encryption methods,” Adv. Opt. Photon. 1(3), 589–636 (2009).
    [CrossRef]
  2. M. Johnson, P. Ishwar, V. Prabhakaran, D. Schonberg, and K. Ramchandran, “On compressing encrypted data,” IEEE Trans. Signal Process. 52(10), 2992–3006 (2004).
    [CrossRef]
  3. A. Alfalou, A. Loussert, A. Alkholidi, and R. El Sawda, “System for image compression and encryption by spectrum fusion in order to optimise image transmission,” FGCN 2007, IEEE Proceeding, ISBN: 0–7695–3048–6, Vol. 2, 2007, pp. 593–596.
  4. A. Alfalou and C. Brosseau, “Exploiting root-mean-square time-frequency structure for multiple-image optical compression and encryption,” Opt. Lett. 35(11), 1914–1916 (2010).
    [CrossRef] [PubMed]
  5. T. J. Naughton, J. B. McDonald, and B. Javidi, “Efficient compression of fresnel fields for Internet transmission of three-dimensional images,” Appl. Opt. 42(23), 4758–4764 (2003).
    [CrossRef] [PubMed]
  6. P. Refrégier and B. Javidi, “Optical image encryption based on input plane and Fourier plane random encoding,” Opt. Lett. 20(7), 767–769 (1995).
    [CrossRef] [PubMed]
  7. B. Javidi, C. M. Do, S.-H. Hong, and T. Nomura, “Multi-spectral holographic three-dimensional image fusion using discrete wavelet transform,” J. Disp. Technol. 2(4), 411–417 (2006).
    [CrossRef]
  8. See, e.g. K. R. Rao and P. Yip, Discrete Cosine Transform: Algorithms, Advantages, Applications, (Academic Press, 1990), and http://www.jpeg.org/ .
  9. B. Javidi, ed., Optical and Digital Techniques for Information Security, (Springer Verlag, New York, 2005).
  10. Y. Frauel, A. Castro, T. J. Naughton, and B. Javidi, “Resistance of the double random phase encryption against various attacks,” Opt. Express 15(16), 10253–10265 (2007).
    [CrossRef] [PubMed]

2010 (1)

2009 (1)

2007 (1)

2006 (1)

B. Javidi, C. M. Do, S.-H. Hong, and T. Nomura, “Multi-spectral holographic three-dimensional image fusion using discrete wavelet transform,” J. Disp. Technol. 2(4), 411–417 (2006).
[CrossRef]

2004 (1)

M. Johnson, P. Ishwar, V. Prabhakaran, D. Schonberg, and K. Ramchandran, “On compressing encrypted data,” IEEE Trans. Signal Process. 52(10), 2992–3006 (2004).
[CrossRef]

2003 (1)

1995 (1)

Alfalou, A.

Brosseau, C.

Castro, A.

Do, C. M.

B. Javidi, C. M. Do, S.-H. Hong, and T. Nomura, “Multi-spectral holographic three-dimensional image fusion using discrete wavelet transform,” J. Disp. Technol. 2(4), 411–417 (2006).
[CrossRef]

Frauel, Y.

Hong, S.-H.

B. Javidi, C. M. Do, S.-H. Hong, and T. Nomura, “Multi-spectral holographic three-dimensional image fusion using discrete wavelet transform,” J. Disp. Technol. 2(4), 411–417 (2006).
[CrossRef]

Ishwar, P.

M. Johnson, P. Ishwar, V. Prabhakaran, D. Schonberg, and K. Ramchandran, “On compressing encrypted data,” IEEE Trans. Signal Process. 52(10), 2992–3006 (2004).
[CrossRef]

Javidi, B.

Johnson, M.

M. Johnson, P. Ishwar, V. Prabhakaran, D. Schonberg, and K. Ramchandran, “On compressing encrypted data,” IEEE Trans. Signal Process. 52(10), 2992–3006 (2004).
[CrossRef]

McDonald, J. B.

Naughton, T. J.

Nomura, T.

B. Javidi, C. M. Do, S.-H. Hong, and T. Nomura, “Multi-spectral holographic three-dimensional image fusion using discrete wavelet transform,” J. Disp. Technol. 2(4), 411–417 (2006).
[CrossRef]

Prabhakaran, V.

M. Johnson, P. Ishwar, V. Prabhakaran, D. Schonberg, and K. Ramchandran, “On compressing encrypted data,” IEEE Trans. Signal Process. 52(10), 2992–3006 (2004).
[CrossRef]

Ramchandran, K.

M. Johnson, P. Ishwar, V. Prabhakaran, D. Schonberg, and K. Ramchandran, “On compressing encrypted data,” IEEE Trans. Signal Process. 52(10), 2992–3006 (2004).
[CrossRef]

Refrégier, P.

Schonberg, D.

M. Johnson, P. Ishwar, V. Prabhakaran, D. Schonberg, and K. Ramchandran, “On compressing encrypted data,” IEEE Trans. Signal Process. 52(10), 2992–3006 (2004).
[CrossRef]

Adv. Opt. Photon. (1)

Appl. Opt. (1)

IEEE Trans. Signal Process. (1)

M. Johnson, P. Ishwar, V. Prabhakaran, D. Schonberg, and K. Ramchandran, “On compressing encrypted data,” IEEE Trans. Signal Process. 52(10), 2992–3006 (2004).
[CrossRef]

J. Disp. Technol. (1)

B. Javidi, C. M. Do, S.-H. Hong, and T. Nomura, “Multi-spectral holographic three-dimensional image fusion using discrete wavelet transform,” J. Disp. Technol. 2(4), 411–417 (2006).
[CrossRef]

Opt. Express (1)

Opt. Lett. (2)

Other (3)

See, e.g. K. R. Rao and P. Yip, Discrete Cosine Transform: Algorithms, Advantages, Applications, (Academic Press, 1990), and http://www.jpeg.org/ .

B. Javidi, ed., Optical and Digital Techniques for Information Security, (Springer Verlag, New York, 2005).

A. Alfalou, A. Loussert, A. Alkholidi, and R. El Sawda, “System for image compression and encryption by spectrum fusion in order to optimise image transmission,” FGCN 2007, IEEE Proceeding, ISBN: 0–7695–3048–6, Vol. 2, 2007, pp. 593–596.

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Figures (4)

Fig. 1
Fig. 1

Synoptic diagram illustrating the fusion method of multiple images, n is the number of target images. Rotation, shift, and 4 by 4 grouping constitute a first level of encryption.

Fig. 2
Fig. 2

Principle of the compression technique used in this work: (a) the target image, (b) the DCT and the low-pass filter, (c)-(d) example of a filtered DCT divided in separate areas, (d) the filtered and quantized DCT.

Fig. 3
Fig. 3

Comparison of the reconstructed Lena’s picture with: (a) the JPEG compression and (b) the present algorithm.

Fig. 4
Fig. 4

Illustrating the three levels of encryption in our method: (a) the original target image, (b) the encrypted image with three levels of encryption (one of them is a fingerprint), (c) the modified fingerprint used for encryption of the second block of target images, and (d) simulation result when the cipher knows the principle of our method and when the access to the system is granted to him or her.

Tables (1)

Tables Icon

Table 1 Compression and reconstruction results obtained by increasing the number of target images and decreasing the number of bits for encoding the different areas of the filtered and quantized DCTs.

Equations (3)

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( F s x ,F s y )=( I s x n , I s y n ).
V zon e l ' ( i,j )=round( ( 2 m1 1 ) V zon e l ( i,j ) Max ( V zon e l ) ).
T c =( 1 n b out n b in )100,

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