:
Watermarking is a process of embedding a message inside a digital signal like an image, video or text. It is used for several key reasons such as authenticity verification, ownership recognition and hidden communication. In this paper, we discuss about
image watermarking, where secret messages are stored in images.
Introduction:
We propose a dual watermarking approach, which is based on Discrete Cosine Transform, Discrete Wavelet Transform and Singular Value Decomposition methods. This paper considers one watermark as robust and other water mark as fragile.
Method:
The robust watermark is embedded in Discrete Wavelet Transform- Singular Value Decomposition - domain and is used
to transmit hidden messages. The fragile watermark is embedded in Discrete Cosine Transform domain and is used for verification
of secret message of the robust watermark. The proposed algorithm is tested in the experimental results section and shows promising results against denoising, rotation, translation and cropping attacks.
Result:
The results show that the performance of the proposed algorithm in terms of mean squared error, structural similarity and
peak signal to noise ratio is S4considerable as compared with the existing methods.
Discussion:
We present the comparison results with Himanshu et. al. in table 10, from which we can see that our method performs
better with gaussian noise and rotational attack only lacking with Salt and Pepper noise. Fig. 7 and Fig. 8, in terms of resulting
PSNR shows the variation of noise variance and degree of rotation. From the graphs it is evident that out method performs better
against Gaussian and rotational attack.
Conclusion:
In this paper a dual watermarking method is proposed in which one watermark is fragile which is called as authentication watermark whereas the other watermark is robust and is called as the information watermark. The authentication watermark is
embedded in the fractional part of DCT domain in the cover image and the information watermark is embedded in the diagonal vector of the LL sub-band.
Comparison of Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Stationary Wavelet Transform (SWT) based Satellite Image Fusion Techniques
