Visible Image Watermarking Based on Image Fusion with Shearlet Transform Using Genetic Algorithm

Yıl 2017, Cilt: 13 Sayı: 3, 1 - 9, 31.12.2017

Harun Akbulut , Veysel Aslantas , Hasan Ulutaş

Öz

In this paper, visible image watermarking based on
image fusion with shearlet transform using genetic algorithm is proposed. The
proposed method consists of three steps. First of all steps, shearlet transform
is separately applied to host image and mark image.  Secondly, weighted image fusion rate is determined
by using genetic algorithm and fused image is obtained according to optimized
image fusion rate. Finally, visible watermarked image is obtained by applying
inverse shearlet transform to fused image. Visible watermarked image is
assessed by quality metrics and these results show that the proposed method is
satisfactory for visible image watermarking based on image fusion with shearlet
transform using genetic algorithm.

Anahtar Kelimeler

Genetic Algorithm, Image Fusion, Image Watermarking, Shearlet Transform

Kaynakça

• 1. Aslantaş, Özer ve arkadaşları, “Genetik Algoritma ile Ayrık Kosinüs Dönüşümü Tabanlı Yeni Bir Resim Damgalama Yöntemi”,IEEE, 2009.
• 2. Wei, Li, and others, “Image Watermarking Based on Genetic Algorithm”, China, 2006.
• 3. Zhang and Hu, “Curvelet Image Watermarking Using Genetic Algorithms”, Congress on Image and Signal Processing, China, 2008.
• 4. Jagadeesh, Kumar ve arkadaşları, “Image Watermarking Scheme Using Singular Value Decomposition,Quantization and Genetic Algorithm”, International Conference on Signal Acquisition and Processing, India, 2010
• 5. Aslantas V, Kurban R, "Genetik Algoritma Kullanarak Görüntü Kaynaştırma Tabanlı Görünür Damgalama", 3. Uluslararası Katılımlı Bilgi Güvenliği ve Kriptoloji Konferansı, Ankara, 2008.
• 6. I.J.Cox, M.L.Miller, and J.A. Bloom, “Digital Watermarking,” Morgan Kaufmann Publishers, 2002.
• 7. J.S.Pan, H.C.Huang, and L.C.Jain, “Intelligent Watermarking Techniques,” World Scientific Publishing Company, 2004.
• 8. C.H.Huang and J.L.Wu, “A watermark optimizationtechnique based on genetic algorithms,” Proceedings of the SPIE-Visual Communications Image Processing, vol.3971, pp.516-523, February 2000.
• 9. Aslantas, V. “A singular-value decomposition-based image watermarking using genetic algorithm”, AEU -International Journal of Electronics and Communications, Volume 62, Issue 5, 386-394, 2008.
• 10. R. Kurban, “Resim Uzayında Blok Seçmeye Dayalı Yeni Görüntü Birleştirme Yöntemleri”, Doktora Tezi, Erciyes Üniversitesi, Kayseri, 2012.
• 11. Lü L, Zhao J and Sun H, "Multi-Focus Image Fusion Based on Shearlet and Local Energy ", 2nd International Conference on Signal Processing Systems, IEEE, 2010.
• 12. Q. G. Miao, C. S. Shi, P. F. Xu, M. Yang, Y. B. Shi, “Multifocus image fusion algorithm based on shearlets”, Chinese Optics Letters 9(4),, pp. 041001-041005, 2011.
• 13. K. Guo, D. Labate, “Optimally sparse multi-dimensional representation using shearlet”, SIAM Journal of Mathematical Analysis and Application 39, pp. 298-318, 2007.
• 14. G. Easley, D. Labate, W. Q. Lim, “Sparse directional image representation using the discrete shearlet transforms”, Applied and Computational Harmonic Analysis 25, pp. 25-46, 2008.
• 15. G. R. Easley, W. Lim and D. Labate, “Sparse Directional Image Representations using the Discrete Shearlet Transform”, Appl. Comput Harmon.Anal pp.25-46,2008.
• 16. W. Lim, “The Discrete Shearlet Transform : A New Directional Transform and Compactly Supported Shearlet Frames”, IEEE Trans. Image Proc.vol. 19,pp.1166-1180,2010.