Table 4 NCC of watermark images extracted from different attacks.
From: An adaptive robust watermarking scheme based on chaotic mapping
Type of attack | Airplane | Baboon | Goldhill | House | Lake | Peppers |
---|---|---|---|---|---|---|
No attack | 1 | 1 | 1 | 1 | 1 | 1 |
Salt and pepper noise (m = 0, v = 0.01) | 0.9920 | 0.9968 | 0.9929 | 0.9947 | 0.9969 | 0.9951 |
Salt and pepper noise (m = 0, v = 0.05) | 0.9337 | 0.9740 | 0.9451 | 0.9508 | 0.9600 | 0.9616 |
Gaussian noise (m = 0, v = 0.01) | 0.9772 | 0.9855 | 0.9681 | 0.9812 | 0.9859 | 0.9779 |
Gaussian noise (m = 0, v = 0.05) | 0.8380 | 0.8927 | 0.8545 | 0.8746 | 0.8824 | 0.9086 |
Speckle noise (m = 0, v = 0.01) | 0.9841 | 0.9947 | 0.9919 | 0.9925 | 0.9968 | 0.9981 |
Speckle noise (m = 0, v = 0.05) | 0.8653 | 0.9643 | 0.9367 | 0.9300 | 0.9540 | 0.9812 |
Sharpening | 0.9733 | 0.8996 | 0.9583 | 0.9591 | 0.9429 | 0.9711 |
Gaussian filter (3\(\times \)3) | 0.9963 | 0.9599 | 0.9933 | 0.9930 | 0.9896 | 0.9961 |
Gaussian filter (5\(\times \)5) | 0.9932 | 0.9347 | 0.9879 | 0.9867 | 0.9806 | 0.9930 |
Mean filter (3\(\times \)3) | 0.9948 | 0.9466 | 0.9905 | 0.9902 | 0.9852 | 0.9946 |
Mean filter (5\(\times \)5) | 0.9818 | 0.8775 | 0.9690 | 0.9645 | 0.9496 | 0.9816 |
Rotation (5\(^\circ \)) | 0.8984 | 0.9658 | 0.9445 | 0.9315 | 0.9622 | 0.9886 |
Rotation (10\(^\circ \)) | 0.8445 | 0.8771 | 0.8463 | 0.8412 | 0.8913 | 0.9763 |
Flip vertical | 1 | 1 | 1 | 1 | 1 | 1 |
Cropping (10%) | 0.9870 | 0.9975 | 0.9979 | 0.9920 | 0.9936 | 0.9975 |
Cropping (20%) | 0.9239 | 0.9664 | 0.9831 | 0.9642 | 0.9155 | 0.9859 |
JPEG (QF=90) | 0.9988 | 0.9965 | 0.9991 | 0.9999 | 0.9996 | 0.9999 |
JPEG2000 (QF=90) | 0.9986 | 0.9624 | 0.9954 | 0.9968 | 0.9921 | 0.9984 |
Gamma correction (gama=0.8) | 0.9800 | 0.9748 | 0.9883 | 0.9839 | 0.9821 | 0.9860 |