Optimal image watermarking scheme based on chaotic map and quaternion wavelet transform

Abstract

In this paper, an intelligent watermarking scheme optimized by adaptive differential evolution (ADE) is proposed based on chaotic map and quaternion wavelet transform (QWT). Watermark is first scrambled by a piecewise linear chaotic map to increase security and then inserted into the real QWT amplitude coefficients intelligently. ADE algorithm is explored to optimize the watermarking parameter (i.e., scaling factors) automatically. The experimental results demonstrate the high robustness against common signal processing operations, especially geometrical distortions of the proposed algorithm. Comparison results also indicate the superiority of the proposed algorithm over the existing watermarking algorithm.

Digital watermarking scheme for colour remote sensing image based on quaternion wavelet transform and tensor decomposition

“…For example, the QFT, which overcomes the shift variance problem by providing multiple phase information, has demonstrated high robustness against geometric distortions. However, this transform is still sensitive to noise manipulations because it lacks multiscale characteristics . To solve this problem, the quaternion wavelet transform (QWT) has been applied to the watermarking research recently.…”

“…Therefore, the QWT‐based watermarking method not only addresses the common drawbacks in standard wavelet transforms by providing the shift‐invariant feature but also exhibits superiority over the QFT because of its multiscale property . For instance, the QWT‐based watermarking method has demonstrated high robustness against many signal processing manipulations . However, such QWT‐based watermarking method still suffers from implementation issues and is vulnerable to mixed image manipulations …”

“…For example, Niu et al proposed modelling the statistical distribution of the host image with a Gaussian mixture model that was then used to select the significant wavelet coefficients of the host image for data hiding . Lei et al proposed a watermarking scheme based on combining the QWT with SVD . However, when combining the QWT and statistical feature of the host image, some drawbacks still exist because they often work within luminous or individual colour bands.…”

A Normalized SVD based Image Watermarking with an Enhanced Robustness and Imperceptibility

“…These methods generally are lessrobust to image and signal processing attacks and requiredlow computational efforts, while frequency domain methodstransform the representation of spatial domain into thefrequency domain and then modify its frequency coefficientsto embed the watermark.There are many transform domainwatermarking techniques such as discrete cosine transforms(DCT) [12], discrete Fourier transforms (DFT) [13][14],discrete wavelet transforms (DWT) [15][16][17], and singularvalue decomposition (SVD) [2,[18][19][20]. These methods typicallyprovide higher image imperceptibility and are muchmore robust to image manipulations, but the computationalcost is higher than spatial domain watermarking methods.The performance of watermarking methods was furtherimproved by combining two or more transformations [21][22][23][24][25][26][27][28][29][30][31][32][33].The singular value decomposition (SVD) is extensivelyused in image watermarking field in recent years due toits features. However, various researchers pointed out thefalse positive detection problem in most of the SVD-based algorithms [7,[34][35].…”

“…Also, these schemes are applicable only for the black and white watermark. A watermarking scheme proposed in [32] is based on thefact that SVD subspace (left and right singular vectors)can preserve a significant amount of information aboutan image. Therefore, it embeds the principal component,multiplication of left singular vector matrix and the singularvalue matrix, of watermark into the host image instead ofsingular values of the watermark.…”