RDWT Based Digital Image Watermarking and Extraction Using ICA

In recent years, watermarking has become an attractive field in the areas like copyright protection, image authentication. Many literatures have reported about Discrete Wavelet Transform (DWT) watermarking techniques for data security. However, DWT based watermarking schemes are found to be less robust against image processing attacks and the shift variance of Wavelet Packet Transform (WPT) causes inaccurate extraction. In this paper, an attempt is made to develop a watermarking scheme based on RDWT and extraction using Independent Component Analysis (ICA). Various ICA like Fast ICA, Radical ICA, Pearson ICA, Jade ICA, Maximum Likelihood ICA, Mean Field ICA and Kernel ICA are proposed and implemented for extraction. Simulation results show that the proposed scheme produces high Peak Signal to Noise Ratio (PSNR) values over other transform techniques like DWT and WPT. Also results reveal that Fast ICA produces better similarity measure and Mutual Information over other ICA methods.