Dynamic energy enabled differentiation (DEED) image watermarking based on human visual system and wavelet tree classification

2009 ◽  
Vol 52 (2-3) ◽  
pp. 385-406 ◽  
Author(s):  
Min-Jen Tsai
2008 ◽  
Vol 88 (1) ◽  
pp. 174-188 ◽  
Author(s):  
Huiyan Qi ◽  
Dong Zheng ◽  
Jiying Zhao

Author(s):  
Ali Al-Haj ◽  
Aymen Abu-Errub

The excellent spatial localization, frequency spread, and multi-resolution characteristics of the discrete wavelets transform (DWT), which are similar to the theoretical models of the human visual system, facilitated the development of many imperceptible and robust DWT-based watermarking algorithms. However, there has been extremely few proposed algorithms on optimized DWT-based image watermarking that can simultaneously provide perceptual transparency and robustness Since these two watermarking requirements are conflicting, in this paper we treat the DWT-based image watermarking problem as an optimization problem, and solve it using genetic algorithms. We demonstrate through the experimental results we obtained that optimal DWT-based image watermarking can be achieved only if watermarking has been applied at specific wavelet sub-bands and by using specific watermarkamplification values.


2017 ◽  
Vol 77 (11) ◽  
pp. 13531-13555 ◽  
Author(s):  
Youssra Lakrissi ◽  
Abderrahim Saaidi ◽  
Abdelouahed Essahlaoui

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