Semisubsampled wavelet transform based image watermarking

Abstract

In this paper, we develop a novel transform which is called semisubsampled wavelet transform (SSWT) and employ it to image watermarking. Combining nonsubsampled pyramid (NSP) with critically sampled wavelet transform (WT) to construct filter banks of SSWT. The result of the nonsubsapled part is a flexible multiscale and shift invariant image decomposition that can be efficiently implemented via the a trous algorithm. Because of the shift invariance can efficiently remove the Gibbs phenomenon, the imperceptibility and robustness of watermark can be improved simultaneously. The experimental results show that the proposed blind watermarking scheme is robust against JPEG compression, Gaussian noise, Wiener filtering and median filtering attacks. The comparison analysis demonstrates that our scheme has better performance than the watermarking schemes reported recently.