Texture Directionality-Based Digital Watermarking in Nonsubsample Shearlet Domain

Table 6

Experimental results for the “Gaussian” white noise attack.

Test image	Var = 0.001; SSIM/NC/BER	Var = 0.005; SSIM/NC/BER	Var = 0.01; SSIM/NC/BER	Var = 0.05; SSIM/NC/BER
Lena	0.6183/0.9960/0.2209	0.3432/0.9951/0.2441	0.2481/0.9932/0.3418	0.0989/0.9907/0.4639
Snow	0.6721/0.9941/0.2930	0.4617/0.9897/0.5127	0.3710/0.98191/0.9033	0.3709/0.9751/1.2451
Snow2	0.6239/0.9985/0.0732	0.3641/0.9966/0.1709	0.2643/0.9912/0.4395	0.1009/0.9883/0.5859
Crowd	0.7400/0.9971/0.1465	0.5013/0.9956/0.2197	0.3962/0.9951/0.2441	0.1869/0.9941/0.2930
Woman	0.6985/0.9980/0.0977	0.4140/0.9961/0.1953	0.3029/0.9951/0.2441	0.1217/0.9893/0.5371
Lake	0.8259/0.9946/0.2686	0.5657/0.9937/0.3174	0.4452/0.9922/0.3906	0.2147/0.9917/0.4150
Plane	0.6115/0.9785/1.0742	0.8480/0.9946/0.2686	0.9851/0.9834/0.8301	0.9925/0.9634/1.8311
Baboon	0.8925/0.9858/0.7080	0.3671/0.9854/0.7324	0.2853/0.9814/0.9277	0.1389/0.9805/0.9766
Peppers	0.6661/0.9966/0.1709	0.3805/0.9902/0.4883	0.2802/0.9897/0.5127	0.1190/0.9717/1.4160
Scenery	0.8961/0.9961/0.1953	0.7407/0.9956/0.2197	0.6310/0.9883/0.5859	0.3370/0.9780/1.0986
Man	0.7385/0.9951/0.2441	0.4691/0.9941/0.2930	0.3514/0.9922/0.3906	0.1454/0.9917/0.4150
Bridge	0.8812/0.9980/0.0977	0.6653/0.9961/0.1953	0.5342/0.9951/0.2441	0.2471/0.9717/1.4160