PSO-Optimized Watermarking Using Lifting Wavelet Transform and SVD for Enhanced Image Security

Rapid development of the digital technology and internet has made copyright protection and ownership verification of digital audio data hot research topics that have attracted a lot of interest from different parties. Since the traditional audio protection algorithms cannot solve all the problems of audio copyright protection and digital right management (DRM) due to the unique audio data features and algorithm limitations, this thesis is proposed to address the issue of audio copyright protection using watermarking techniques. Firstly, a new perception-based watermarking scheme for MPEG-4 scalable to lossless (SLS) audio is proposed. Under the control of the psychoacoustic model, the significant part of integer modified discrete cosine transform (IntMDCT) coefficients are adaptively modified during MPEG-4 SLS audio compression taking robustness, imperceptibility and security into consideration. The chaotic watermark generated by chaos is then embedded to ensure security. Moreover, the adaptive spread spectrum (SS) method is exploited to further optimize the tradeoff between robustness and transparency of this scheme. Secondly, a blind and robust audio watermarking scheme based on singular value decomposition (SVD) – followed by discrete cosine transform (DCT) with the synchronization code technique is proposed. A binary watermark is embedded into the high frequency band of the SVD-DCT block. Chaotic sequence is adopted as the synchronization code and inserted into the host signal. Thirdly, a new and robust audio watermarking scheme based on lifting wavelet transform (LWT) and SVD is proposed. Specifically, the watermark data is efficiently inserted in the low coefficient of the frequency subband of LWT audio taking advantage of both SVD and quantization index modulation (QIM). Furthermore, the synchronization code technique is also integrated in the hybrid LWT-SVD audio watermarking method. Finally, a particle swarm optimization (PSO) and SVD based audio watermarking scheme is proposed. The watermark is embedded by modifying singular values (SVs) of the host audio signal with the SS method. The designed optimization technique employs PSO to search for the optimal watermark strength by continuously adjusting the fitness values so that the conflicting requirements of robustness and imperceptibility of the watermark are satisfied optimally. Moreover, the proposed scheme has the flexibility to include or remove various watermarking attacks during training for optimization. The experimental results validate the practicality of the proposed methods and show that the proposed algorithms are very robust to typical signal manipulations. Furthermore, the results of comparison with other similar state-of-the-art audio watermarking techniques indicate that the proposed algorithms are more robust against most common signal processing attacks while preserving good imperceptibility.

In this paper, a new optimal watermarking scheme based on singular value decomposition (SVD) and lifting wavelet transform (LWT) using multi-objective genetic algorithm optimization (MOGAO) is presented. The singular values of the watermark is embedded in a detail subband of host image. To achieve the highest possible robustness without losing watermark transparency, multiple scaling factors (MSF) are used instead of single scaling factor (SSF). Determining the optimal values of the MSF's is a difficult problem. However, to find this values a multi-objective genetic algorithm optimization is used. Experimental results show a much improved performance in term of transparency and robustness of the proposed method compared to others methods.

Security and authentication of the people information is effectively provided through various watermarking algorithms. Most of the conventional watermarking algorithms have their own drawbacks in maintaining the quality and security of the image against various attacks. In order to overcome the above stated issues, a watermarking technique based on optimization is required for preserving image quality. In this paper, singular value decomposition (SVD) based digital image watermarking (DIW) scheme is proposed in hybrid discrete cosine transform (DCT) and discrete wavelet transform (DWT) using optimization algorithms like particle swarm optimization (PSO) and Jaya algorithm. The watermark image (WI) is embedded into low frequency DWT sub-band of DCT of cover image. PSO and Jaya algorithms are applied to improve the security threats and quality by assessing the fitness function. The work involves in utilizing the feature points in embedding of watermarks and analyzing the impact of various types of attacks with respect to image quality. The performance parameters like peak signal to noise ratio (PSNR), Structural Similarity Index (SSIM) and correlation coefficient of fitness function given by PSO and Jaya algorithm.

Prior research studies have shown that the peak signal to noise ratio (PSNR) is the most frequent watermarked image quality metric that is used for determining the levels of strength and weakness of watermarking algorithms. Conversely, normalised cross correlation (NCC) is the most common metric used after attacks were applied to a watermarked image to verify the strength of the algorithm used. Many researchers have used these approaches to evaluate their algorithms. These strategies have been used for a long time, however, which unfortunately limits the value of PSNR and NCC in reflecting the strength and weakness of the watermarking algorithms. This paper considers this issue to determine the threshold values of these two parameters in reflecting the amount of strength and weakness of the watermarking algorithms. We used our novel watermarking technique for embedding four watermarks in intermediate significant bits (ISB) of six image files one-by-one through replacing the image pixels with new pixels and, at the same time, keeping the new pixels very close to the original pixels. This approach gains an improved robustness based on the PSNR and NCC values that were gathered. A neural network model was built that uses the image quality metrics (PSNR and NCC) values obtained from the watermarking of six grey-scale images that use ISB as the desired output and that are trained for each watermarked image’s PSNR and NCC. The neural network predicts the watermarked image’s PSNR together with NCC after the attacks when a portion of the output of the same or different types of image quality metrics (PSNR and NCC) are obtained. The results indicate that the NCC metric fluctuates before the PSNR values deteriorate.

Watermarking is crucial for protecting medical images, guaranteeing data integrity and authenticity in telemedicine, especially for rural healthcare facilities with limited computational power. This paper introduces a lightweight watermarking scheme that performs a comparative study of Lifting Wavelet Transform (LWT) versus Discrete Wavelet Transform (DWT), both combined with Discrete Cosine Transform (DCT), to achieve optimal imperceptibility, robustness, and computational efficiency. The comparison of LWT and DWT is essential because LWT has lower computational complexity and memory usage, hence more appropriate for resource-limited environments than DWT, and without the use of Singular Value Decomposition (SVD) to further reduce processing requirements and improve compatibility with low-power devices. The suggested approach adopts adaptive embedding against texture complexity, secure synchronization patterns with m-sequences and Barker codes, and geometric correction utilizing ORB for guaranteed watermark extraction under attacks from JPEG compression, Gaussian noise attack, rotation attack, median filter attack, and Gaussian blur. A new error correction code interleaved with majority voting is employed to increase the watermark’s strength. Tested at various embedding strengths, the scheme attains Peak Signal to Noise Ratio (PSNR) values over 40 dB and Structural Similarity Index (SSIM) values above 0.95, signifying extremely little visual degradation. Low Bit Error Rates (BER) and high Normalized Correlation (NC) in various attack scenarios validate its success. This computational-friendly solution is designed to arm remote healthcare organizations with limited computer ability to reliably authenticate and attest to medical images, meeting severe telemedicine demands.

Huge expansion of multimedia data in internet has given rise to various unauthorized use and modification. This authenticity problem is equally a constraint in the defense information transmission along with secured transmission. Digital watermarking shows a valid solution to the above problem, since it makes possible authentication and secure transmission of confidential information or any sort of control signals. We introduce a new highly secured Digital Watermarking Algorithm especially for Binary Watermark using Lifting Wavelet Transform (LWT) and Singular Value Decomposition (SVD). Our main motive is to keep watermark intact to the original image and also to increase the data embedding & extraction rate. We use only the LL sub-band (containing an approximation of the image) of the cover image obtained from Lifting Wavelet Transform and then apply Singular Value Decomposition to embed the binary watermark. Moreover due to usage of lifting based wavelet transform and SVD the hardware implementation is better.

Digital Image Watermarking provides a successful method for content authentication and copyright protection. Thus, it has significant scope in today's era due to the rapid growth of internet users. The watermark should be robust and reliable in addition to being imperceptible to the human eye. In this paper, a hybrid singular value decomposition (SVD) and discrete wavelet transform (DWT) based watermarking scheme is presented. The SVD used in this scheme is a variant of the traditional SVD and is called shuffled SVD (SSVD). The cover image is decomposed into four sub-bands (LL, HL, LH, HH) using DWT. The LL subband is further divided into blocks of appropriate size. The principle components of the watermark image obtained after applying SSVD are embedded in various blocks of the LL sub-band. The proposed scheme shows significant robustness in addition to being false positive free.

In this proposed work, a dual image watermarking algorithm is used to protect the data against copyright violations. In this work, the DICOM image is used as a host image. Two watermark images used are the MNNIT logo and the personal data of the patient. This method utilizes the advantages of Schur decomposition, lifting wavelet transform (LWT), discrete cosine transform (DCT) and singular value decomposition (SVD). The scaling factor is a vital parameter of watermarking technique. The firefly optimization technique is used to get the optimized scaling factor. The Speeded-up robust features (SURF) are used for watermarking authentication. To evaluate the performance of the proposed algorithm, peak signal-to-noise ratio (PSNR), normalized correlation coefficient (NCC), and structural similarity index measurement (SSIM) are used. The proposed method is tested against various attacks such as Salt and Pepper noise, Gaussian noise, Gaussian low pass filter, Average filter, Median filter, Histogram equalization, Sharpening, Rotation and Region of interest filtering. The proposed algorithm shows a high level of robustness and imperceptibility. It is found that the features of the input host image and the watermarked image are matching correctly on applying the SURF technique.

Digital image watermarking is one of the important method of copyright protection and rightful ownership of the digital image and video. In this paper, the existing algorithm based on DWT-SVD is improved and made adaptive with particle swarm optimization (PSO) which increases the robustness and imperceptibility. Existing as well as proposed algorithm based on PSO creates diagonal line in the extracted watermark image against some of the noise attacks. Further to remove diagonal line from the extracted watermark image an algorithm based on PSO and Arnold transform is proposed. Both proposed algorithms (PSO and AT-PSO) are implemented and tested with different types of cover images. The comparative analysis of these two proposed algorithms is carried out with the existing algorithm. The comparative analysis shows that under most of noise attacks both the proposed algorithms outperform over the existing algorithm in terms of Peak Signal to Noise Ratio (PSNR) and Normalized Similarity Ratio (NSR). Moreover, the imperceptibility offered by Arnold transform based algorithm is better as compared to the other proposed algorithm. Robustness of both the proposed algorithms is close to each other.

Digital image watermarking is one of the largest research fields, and it plays a vital role in digital information authentication and security. Based on the study of watermarking systems, the whole process may be segregated into the processes of watermark embedding and extraction. In this paper, a review of the theoretical and experimental analysis and performance measurement of representative digital image watermarking systems in spatial and transform domains is presented. The significant characteristics of the digital image watermarking scheme are robustness, capacity, imperceptibility, the security of the hiding place, and false-positive of the watermarking algorithm. Comparison of the different watermarking techniques such as the least significant bit (LSB), singular value decomposition (SVD), the discrete wavelet transform (DWT), and the discrete cosine transform (DCT) is presented in a tabular form. A detailed discussion along with an algorithm for digital image encryption/decryption through embedding and extraction is given. A brief comparison of their relative advantages and disadvantages is also noted in this paper.KeywordsInformation hidingWatermarkingSecurityAttacksRobust

This contribution applies tools from the information theory and soft computing (SC) paradigms to the embedding and extraction of watermarks in aerial remote sensing (RS) images to protect copyright. By the time 5G came along, Internet usage had already grown exponentially. Regarding copyright protection, the most important responsibility of the digital image watermarking (DIW) approach is to provide authentication and security for digital content. In this paper, our main goal is to provide authentication and security to aerial RS images transmitted over the Internet by the proposal of a hybrid approach using both the redundant discrete wavelet transform (RDWT) and the singular value decomposition (SVD) schemes for DIW. Specifically, SC is adopted in this work for the numerical optimization of critical parameters. Moreover, 1-level RDWT and SVD are applied on digital cover image and singular matrices of LH and HL sub-bands are selected for watermark embedding. Further selected singular matrices SLH and SHL are split into 3×3 non-overlapping blocks, and diagonal positions are used for watermark embedding. Three-level symmetric encryption with low computational cost is used to ensure higher watermark security. A hybrid grasshopper–BAT (G-BAT) SC-based optimization algorithm is also proposed in order to achieve high quality DIW outcomes, and a broad comparison against other methods in the state-of-the-art is provided. The experimental results have demonstrated that our proposal provides high levels of imperceptibility, robustness, embedding capacity and security when dealing with DIW of aerial RS images, even higher than the state-of-the-art methods.

Steganography plays a vital role in the field of covert communication. This paper proposes a novel embedding scheme which embeds secret data adaptively. The proposed scheme employs integer to integer Lifting Wavelet Transforms (LWT) and pixel strength to specify suitable locations for data embedding. The integer LWT eliminates distortions, which is produced because of rounding process in the convolutional wavelet transforms. The performance of the proposed scheme is addressed using image quality metrics based on Peak Signal To Noise Ratio (PSNR) versus embedding ratio. Moreover, Bit Error Rate (BER) is utilized to assess robustness of the scheme. The experimental results show that the proposed is superior over several embedding techniques such as embedding based convolutional wavelet transforms and Lest Significant Bits (LSBs). The range of PSNR is gained between 51.52 and 22.15dB for range of embedding rate between 5% and 35%. Furthermore, the technique results error free for retrieving of secret data. In addition to the above features, the proposed technique increases security level of embedded data due to adaptive embedding process that increases randomly of embedding locations. The proposed scheme can be used in several important applications such as bank tag for authentication, military communications. Also, it can be implemented easily as a hardware chip and combine with covert imaging systems.

The integrity and authenticity of digital images have become more important in past few years with the fast improvement of digital technologies. The integrity of digital images can be achieved by using digital watermarking. In this paper we proposed an efficient image tamper detection method using 3 LSB (last significant bit) watermarking technique. In the proposed algorithm a 12-bit watermark created from each block of host image will embed to last three significant bit of each block. Our proposed method improved Chaluvadi and Prasad's tamper detection rate by 40 percent. To evaluate the proposed method, we performed different types of tamper attacks and demonstrated the result in this paper. The experimental result clearly proved the efficiency of our proposed method.

This paper developed new and efficient image watermarking scheme for copyright protection based on Lifting wavelet transform (LWT) and Bi- dimensional Empirical Mode Decomposition (BEMD). A LWT has been selected because it is fast, less computational cost and maintains the integrity of the recovered watermark. The BEMD transform can separate the image from the most robust to the least sensitive or fragile frequency bands. This advantage is utilised in this study for the purpose of embedding the watermark in the robust part of BEMD, i.e. the residue (r). In addition, the embedding process has been performed in the low sub-band of LWT decomposed image as the low sub-band is more robust to image processing such as JPEG compression. The robust watermark which is grey scale image is decomposed using DWT to enhance the security and select only high sub-band as it has less impact on the quality of the watermarked image. As a result, the original image’s visual quality can be preserved and the concealed watermark could be successfully retrieved even if the watermarked images have undergone severe attacks like JPEG, rotation, Gamma correction, filtering, additive noise, translation, shearing, and scaling. Furthermore, the improved scheme offers greater robustness against many image processing operations, in comparison to the current schemes about copyright protection.

A secure image steganography algorithm based on least significant bit and integer wavelet transform