1. Introduction
In today’s ever-changing world, Internet technology has become an imminent part of our day-to-day life. With the benefits of the Internet, we can easily copy, transmit, distribute, and store information [
1]. However, unfortunately, at the same time, unauthorized usage of personal media content without the permission of owners is also increasing rapidly. Different types of online business sectors face a huge loss every year due to copyright violations. To solve this problem, in recent years, a new form of media content protection has evolved, known as watermarking. A watermark is a piece of information that is embedded into multimedia data such as text, audio, image, and video by the owner to ensure the authenticity of the data. An efficient and effective watermarking method should satisfy three common fundamental requirements: robustness, imperceptibility, and security. First, the watermark image should resist against various attacks. This feature is called robustness. Second, visually, there should be no difference between host and watermarked images. This property is known as imperceptibility [
1]. Finally, the scrambling method is used to shuffle the watermark information before embedding, thereby ensuring the security of the watermark image against numerous attacks. Watermarking can be classified into spatial domain and transform domain techniques. Spatial domain techniques embed a watermark of a given image by modifying its pixels directly. This technique is easy to implement and requires few computational resources [
2,
3]. On the other hand, the transform domain technique is applied to coefficients obtained as the result of a frequency transform of either a whole image or single block-shaped regions of a frame. Discrete cosine transform (DCT) [
4,
5,
6,
7,
8,
9], discrete Fourier transform (DFT) [
10,
11] and discrete wavelet transform (DWT) [
12,
13,
14,
15,
16] are commonly used frequency-domain techniques. Recently, some watermarking methods have been proposed that use various decomposition and transform techniques jointly [
17,
18,
19,
20,
21,
22,
23,
24].
Yashar et al. [
2] suggested a blind gray-scale image watermarking method based on the QR decomposition. In this method, the watermark bit is embedded into the R matrix; however, the imperceptibility is not quite satisfactory. Pizzolante et al. [
3] introduced a novel method that can embed two watermarks into a con-focal 3-D microscopy image; however, the PSNR of this method is not high and the robustness has not been evaluated.
Shuai et al. [
4] suggested a double encryption method, in which the watermark is converted into fractal encoding and then embedded into DCT transformed carrier image; however, their method was only tested against three attacks and the experimental result show that their method do not perform well against Gaussian noise attack. Jingyou et al. [
5] proposed a bimodal structure and iterative selection method in the DCT domain. However, in this method, the PSNR is low. Shabir et al. [
6] proposed a blind watermarking technique in the DCT domain, in which the watermark bit is embedded in the middle band frequency based on coefficient differences in the same position of succeeding blocks. The main disadvantage of this method is that its peak signal to noise ratio (PSNR) is quite low. In [
7], an image watermarking technique using Redundant DWT (RDWT) and DCT domain is proposed, where the binary image is used as a watermark. However, the computational complexity of this method is quite high. Soumitra et al. [
8] introduced a blind digital watermarking in the DCT domain, where multiple watermark images are embedded in the middle band frequency of the host image. However, the PSNR of this method is not high. In [
9], a color image watermarking method based on DCT and DWT is introduced. In this method, the scrambled watermark image is transformed into the DCT domain. After that, transformed watermark information is embedded into four sub-bands region obtained from DWT. The main disadvantage of this method is that it does not provide a good trade-off between robustness and imperceptibility.
In [
10], a DFT-DCT based hybrid image watermarking technique is presented. The watermark bit is scrambled using Arnold transform and is later embedded into middle sub-band frequency. Their method performed well for both imperceptibility and robustness. The main drawback of their method is that it has been tested against very few attacks, such as histogram equalization, JPEG compression, salt and pepper noise, Gaussian noise, etc. In [
11], a DFT and two-dimensional (2D) histogram based hybrid image watermarking is proposed. However, the detector is unable to detect the true watermark image without knowing about the attacks.
In [
12], the authors proposed an image watermarking scheme in the DWT domain. In this paper, the watermark bit is embedded into the coefficients obtained from the three high-frequency sub-bands of first level decomposition but the image quality is degraded with the higher quantization steps. In addition, the authors did not conduct the imperceptibility test. Jinyuan et al. [
13] proposed a digital image watermarking algorithm in the DWT domain, in which the watermark image is scrambled using the logistic map. Then, the watermark bit is embedded into the multilevel DWT coefficients. However, the PSNR of this method is not high and the trade-off between robustness and imperceptibility is not satisfactory. In [
14], the DWT based image watermarking is proposed, where the first-level DWT is applied to a watermark image before embedding. The main flaw of this method is that the host image is considered as the watermark image, which violates the basic requirement of image watermarking. Asma et al. [
15] suggested a DWT-based method in which watermark bit is embedded into the low-frequency band using alpha blending. However, this method is least robust against Gaussian noise. Ravi et al. [
16] introduced a watermarking scheme using DWT and DCT along with Arnold transform, where watermark bit is embedded into a low frequency (LL) band. However, this method has low robustness against cropping attacks.
Qingtang et al. [
17] proposed a color image watermarking method, where the watermark information is embedded into the largest eigenvalue of the Schur decomposed matrix. However, the PSNR of this method is not high and it does not perform well against the cropping attack. Radu et al. [
18] introduced a watermarking method that uses chrip z-transform, DWT, and singular value decomposition (SVD). The disadvantage of this method is that it shows low robustness against the JPEG compression attack. An image watermarking method using DWT and shuffled SVD (SSVD) is suggested in [
19]. In this method, the authors overcame the false positive problem but the PSNR value of this method is not good. In addition, this method is vulnerable against some attacks such as salt and pepper, gamma correction, image sharpening, image cropping, etc. Llukman et al. [
20] presented a hybrid method using RDWT and SVD in which Arnold transform is used to scramble the watermark image to enhance the security. However, the PSNR of the watermarked images is not satisfactory. Yuqi et al. [
21] presented an image watermarking method using DWT, DCT, and SVD. It embeds watermark bits into the singular values of DCT coefficients obtained from the DWT sub-band. However, the robustness result is not good against some attacks such as JPEG compression and low pass filtering. In [
22], an image watermarking method is proposed that can be robust against different types of geometric attacks. However, this method has low robustness against scaling attack.
In [
23], a different type of image watermarking method in the angular radial transform (ART) domain is proposed, in which the watermark bit is embedded in the geometric invariant domain. While these methods are efficient under the scaling or rotation attacks, the performance is still drastically degraded against other geometric attacks such as cropping. Qingtang et al. [
24] suggested a color image watermarking method using LU decomposition, where the watermark information is embedded into the first elements of both second and third rows of the lower triangular matrix. It uses Arnold transform to enhance the watermark security and the pseudo-random MD5 hash function is applied to increase the watermark robustness. However, the PSNR of this method is quite low.
Image scrambling is one of the main features in image watermarking that removes the correlation between pixels of a given image. As a result, the image becomes an insignificant image and can resist malicious attacks to a certain extent [
25]. Arnold transform [
25,
26] is a widely used image scrambling technique. Even though the modified version [
27] is free from periodicity, it still needs a lot of information such as block sequences, block size of the image, etc. while unscrambling the image.
The main limitations of the existing methods are the difficulty in maintaining a good trade-off among robustness, imperceptibility, and security. Moreover, some methods have low robustness, whereas some are less imperceptible or less secured. To overcome these limitations, we propose a blind symmetric image watermarking scheme in canonical and cepstrum domains based on the four-connected t-o’clock scrambling method. To the best of our knowledge, this is the first image watermarking method that utilizes discrete linear canonical transform (DLCT), cepstrum transform (CT), and four-connected t-o’clock scrambling technique jointly. The main characteristics of the proposed method are: (i) it applies DLCT and CT jointly; (ii) it utilizes four-connected t-o’clock scrambling method to enhance the security of the watermark image; (iii) the watermark embedding location is selected after
rotation of the original image; (iv) the watermark bit is selected based on max-heap tree and min-heap tree property; (v) the watermark detection procedure is blind; and (vi) it achieves a good trade-off among security, imperceptibility, and robustness. Simulation results illustrate that the proposed method is highly robust and secured against different attacks. Moreover, the proposed method provides better results in terms of robustness and imperceptibility compared with the recent methods [
17,
24]. The PSNR, structural similarity index (SSIM), and normalized correlation (NC) of the proposed method vary within 51.02–53.39 dB, 0.9969–0.9988, and 0.9567–0.9986, respectively, in contrast to the recent methods whose PSNR, SSIM, and NC range 38.5471–41.5391 dB, 0.9804–0.9975, and 0.6482–0.9998, respectively. Furthermore, in terms of security, the proposed scrambling method shows better performance than some well known scrambling methods.
The remainder of this paper is organized as follows.
Section 2 briefly describes the background information including DLCT and CT.
Section 3 introduces the proposed watermarking method consisting of four-connected t-o’clock scrambling technique, watermark embedding, and extraction processes.
Section 4 provides the experimental results and compares the performance of the proposed method with recent methods in terms of imperceptibility, robustness, and security. Finally, in
Section 5, the conclusion of this paper is presented.