PROJECT TITLE :

A Robust Multiplicative Watermark Detector for Color Images in Sparse Domain

ABSTRACT:

In recent years, digital watermarking has facilitated the protection of copyright info through embedding hidden information into the digital content. In this transient, for the primary time, a blind multichannel multiplicative color image watermarking theme within the sparse domain is proposed. So as to require into account the cross correlation between the coefficients of the color bands in the sparse domain, a statistical model primarily based on the multivariate Cauchy distribution is employed. The statistical model is then used to derive an economical closed-type call rule for the watermark detector. Experimental results and theoretical analysis are presented to validate the proposed watermark detector. The performance of the proposed detector is compared with that of the other detectors. The results demonstrate the improved detection rate and high robustness against the commonly used attacks like JPEG compression, salt and pepper noise, median filtering, and Gaussian noise.