By Komate Amphawan, Philippe Lenca (auth.), Borworn Papasratorn, Nipon Charoenkitkarn, Vajirasak Vanijja, Vithida Chongsuphajaisiddhi (eds.)
This booklet constitutes the complaints of the sixth foreign convention on Advances in info expertise, IAIT 2013, held in Bangkok, Thailand, in December 2013. The 23 revised papers awarded during this quantity have been conscientiously reviewed and chosen from quite a few submissions. They care for all parts regarding utilized info technology.
Read Online or Download Advances in Information Technology: 6th International Conference, IAIT 2013, Bangkok, Thailand, December 12-13, 2013. Proceedings PDF
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Additional resources for Advances in Information Technology: 6th International Conference, IAIT 2013, Bangkok, Thailand, December 12-13, 2013. Proceedings
Chantrapornchai 16. : An Adaptive Steganographic Technique Based on Integer Wavelet Transform. In: Networking and Media Convergence, pp. 111–117 (2009) 17. : High Capacity Image Steganography in Wavelet Domain. In: Consumer Communications and Networking, pp. 1–6 (2010) 18. : Wavelets and Filter Banks: Theory and Design. IEEE Transactions on Signal Processing 40, 2207–2232 (1992) 19. : Secret image sharing scheme with authentication and remedy abilities based on cellular automata and discrete wavelet transform.
2, 251–259 (2012) 8. : Nonlinear Wavelet Methods for Recovery of Signals, Densities, and Spectra from Indirect and Noisy Data. In: Daubechies, I. ) Different Perspectives on Wavelets, Proceeding of Symposia in Applied Mathematics, vol. 47, pp. 173–205. Amer. Math. Soc, Providence (1993) 9. : High Capacity Image Steganography using Wavelet Transform and Genetic Algorithm. In: Multi Conference of Engineers and Computer Scientists, vol. 1 (2011) 10. : Bit-plane decomposition steganography using wavelet compressed video.
It is fast and uses small memory space. The calculation can be done in place. It is also, reversible without edge effect. However, it has some limitation on the discontinuity. The result of wavelet transform is a set of wavelet coefficients. The process of a 2-D Haar-DWT are as follows: ψ ( x) = (−1) c ϕ (2 x − k ) (1) k M −k k where ϕ= the host function that is calculated from , φ jk = φ ( 2 j x − k ) , cM − k = the translation factor. 2 Lifting Based Multi-level Wavelet Transform [1, 3] The lifting scheme is an algorithm used for implementation hardware and software of DWT.