survey

Visual Cryptography(標明紅色的文章表示正在閱讀)

[2009]

* S.J. Shyu, “Image encryption by multiple random grids,” Pattern Recognition, 2009.

[2008]

* J.B. Feng, H.C. Wu, C.S. Tsai, Y.F. Chang and Y.P. Chu, “Visual secret sharing for multiple secrets,” Pattern Recognition, Vol. 41, No. 12, pp. 3572-3581, 2008.

* B.W. Leung, F.Y. Ng and D.S. Wong, “On the security of a visual cryptography scheme for color images,” Pattern Recognition, In Press, Corrected Proof, Available online 17 September 2008.

* C.N. Yang and T.S. Chen, “Colored visual cryptography scheme based on additive color mixing,” Pattern Recognition, Vol. 41, No. 10, pp. 3114-3129, 2008.

* T.H. Chen, K.H. Tsao, “Visual secret sharing by random grids revisited, ” Pattern Recognition, In Press, Accepted Manuscript, Available online 30 November 2008.

* W.P. Fang, “Friendly progressive visual secret sharing,” Pattern Recognition, Vol. 41, No. 4, pp. 1410-1414, 2008.

[2007]

* S.J. Shyu, “Image encryption by random grids,” Pattern Recognition, Vol. 40, No. 3, pp. 1014-1031, 2007.

* S.J. Shyu, S.Y. Huang, Y.K. Lee, R.Z. Wang and K. Chen, “Sharing multiple secrets in visual cryptography,” Pattern Recognition. Vol. 40, No. 12. pp. 3633-3651, 2007.

[1995]

* M. Noar and A. Shamir, “Visual cryptography,” Advances in Cryptology — EUROCRYPT’94, pp. 1-12, 1995.

[1987]

* O. Kafri and E. Keren, Encryption of Pictures and Shapes by Random Grids, Optics Letters, Vol. 12(6), 377-379, 1987.


影像處理課程

[1] Nilamani B, Sukadev M, Circular spatial filtering under high-noise-variance conditions, Computers & Graphics , vol 32, pp. 568-580, 2008

[2] Andrea P, Giovanni R and V. J, Image enhancement via Adaptive Unsharp Masking, IEEE Trans. on Image Processing, vol. 9, no. 3, 2000, pp. 505-510

[3] Wang Z, Bovik AC. A universal image quality index. IEEE Signal Processing Letters 2002;9(3):81–4.

[4] Donoho DL, Johnstone IM. Adapting to unknown smoothness via wavelet shrinkage. Journal of the American Statistical Association 1995;90(432): 1200–24.

[5] Chang S, Yu B, Vetterli M. Adaptive wavelet thresholding for image denoising and compression. IEEE Transactions on Image Processing 2000;9(9): 1532–46.

[6] Chen GY, Bui TD, Krzyzak A. Image denoising using neighboring wavelet coefficients. In: Proceedings of the IEEE international conference on acoustics, speech and signal processing, ICASSP ’04, 2004. p. 917–20.

[7] Mihcak MK, Kozintsev I, Ramchandran K, Moulin P. Low-complexity image denoising based on statistical modeling of wavelet coefficients. IEEE Signal Processing Letters 1999;6(12):300–3.

[8] Tan S, Jiao L. A unified iterative denoising algorithm based on natural image statistical models: derivation and examples. Optics Express 2008;16(2): 975–92.