A blind robust watermarking method based on Arnold Cat map and amplified pseudo-noise strings with weak correlation

TL;DR

This paper introduces a novel blind watermarking technique that enhances security, imperceptibility, and robustness against common attacks by combining Arnold Cat map pre-processing with amplified pseudo-noise strings and frequency domain embedding.

Contribution

It proposes a new watermarking method that integrates Arnold Cat map, weakly correlated pseudo-noise strings, and FDCuT transform for improved robustness and security.

Findings

Outperforms recent methods in robustness tests

Achieves high imperceptibility and security

Effective against noise, compression, and enhancement attacks

Abstract

In this paper, a robust and blind watermarking method is proposed, which is highly resistant to the common image watermarking attacks, such as noises, compression, and image quality enhancement processing. In this method, Arnold Cat map is used as a pre-processing on the host image, which increases the security and imperceptibility of embedding watermark bits with a strong gain factor. Moreover, two pseudo-noise strings with weak correlation are used as the symbol of each 0 or 1 bit of the watermark, which increases the accuracy in detecting the state of watermark bits at extraction phase in comparison to using two random pseudo-noise strings. In this method, to increase the robustness and further imperceptibility of the embedding, the Arnold Cat mapped image is subjected to non-overlapping blocking, and then the high frequency coefficients of the approximation sub-band of the FDCuT transform are used as the embedding location for each block. Comparison of the proposed method with recent robust methods under the same experimental conditions indicates the superiority of the proposed method.