STEGANOGRAPHIC METHOD FOR COLOR IMAGES USING VARIANCE FIELD ESTIMATION AND SCALING FACTOR FOR ENERGY CONSERVATION - Theoretical and Computational Research in the 21st Century - page 105

4. Luo, X. Y.; Wang, D. S.; Wang, P.; and Liu, F. L.; A review on blind detection for im-
age steganography . Signal Processing . 2008, 88, 2138-2157.
5. Kharrazi, M.; Sencar, H.T.; and Memon, N.; Performance study of common image
steganography and steganalysis techniques. J. Electronic Imaging. 2006, 15(4), 1-16.
6. Sajedi, H.; and Jamzad, M.; BSS: Boosted steganography scheme with cover image
preprocessing. Expert Systems Appl . 2010, 37, 7703-7710.
7. Gallegos-Funes, F. J.; Martinez-Valdés, J.; and De-la-Rosa-Vázquez, J. M.; Order sta-
tistics filters in wavelet domain for color image processing. IEEE Sixth Mexican Int.
Conf. Artif Intelligence. 2007, MICAI2007 , 121-130.
8. Carvajal-Gamez, B. E.; Gallegos-Funes, F. J.; and Rosales-Silva, A. J. Color local
complexity estimation based steganographic (CLCES) method. Expert Systems Appl.
2013, 40, 1132-1142.
9. Avcibas, I.; Mmon, N.; and Sankur, B.; Steganalysis using image quality metrics.
IEEE Trans. Image Process. 2003, 12(2), 221-229.
10. Cheddad, A.; Condell, J.; Curran, K.; and Mc Kevitt, P.; Biometric inspired digital
image steganography. 15th IEEE Int. Conf. and Workshop on the Engineering of Com-
puter Based Systems, ECBS2008. Belfast: Northern Ireland; 2008, 159-168.
11. Liu, K. C.; Wavelet-based watermarking for color images through visual masking. Int.
J. Electron. Commun. (AEÜ). 2010, 64, 112-124.
12. Vetterli, M.; and Kočević, J.; Wavelets and Sub-Band Coding. 2th Edn. Prentice-Hall:
New Jersey; 1995 .
13. Petrosian, A.; and Meyers, F.; Wavelets in Signal and Image Analysis. Computational
Imaging and Vision. Springer: Berlin; 2002 .
14. Debnath, L.; Wavelets and Signal Processing. Birkhauser: Berlin; 2002 .
15. Sheng, Y.; The Transforms and Applications Handbook. 2th Edn. CRC Press: London;
2002 .
16. Bogges, A.; and Narcovich, F.; A First Course in Wavelets With Fourier Analysis. 2th
Edn. Wiley: New York; 2009 .
17. Daubechies, I.; Orthornormal bases of compactly supported wavelets. Commun. Pure
Appl. Math. 1988, 41, 909-996.
18. Mallat, S.; A theory for multiresolution signal decomposition: the wavelet representa-
tion. IEEE Trans. Pattern Anal. Mach Int. 1989, 11(7), 674-694.
19. Walker, J.; A Primer on Wavelets and their Scientific Applications. 2th edition. Lon-
don: Chapman and Hall/CRC; 2003 .
20. Carvajal-Gámez, B. E.; Gallegos-Funes, F. J.; López-Bonilla, J. L.; Computational
Techniques and Algorithms for Image Processing. Ed. Berlin: Lambert Academic Pub-
lication; Chapter 13, 2010 .
21. Carvajal-Gámez, B. E.; Gallegos-Funes, F. J.; Rosales-Silva, A. J.; and López-Bo-
nilla, J.; Adjust of energy with compactly supported orthogonal wavelet for stegano-
graphic algorithms using the scaling function. Int. J. Phys. Sci. 2013, 8(4), 157-166.
22. Alata, O.; and Quintard, L.; Is there a best color space for color image characterization
or representation based on multivariate Gaussian mixture model? Comput Vis. Image
Und. 2009, 113, 867-877.
23. De Queiroz, R. L.; Reversible color-to-gray mapping using sub-band domain textur-
ization. Pattern Recognit. Lett. 2010, 31, 269-276.