Discrete Wavelet Transform Singular Value Decomposition Research Articles

Robust digital image watermarking scheme with a fractional-order discrete-time chaotic scheme and DWT-SVD transform

A robust digital image watermarking system with a fractional-order discrete-time chaotic system and discrete wavelet transform-singular value decomposition is presented. The inclusion method inserts an encrypted image into the dynamics of an integer-order discrete-time chaotic system and the resulting cipher serves as a host image watermark. A watermarking function (DWT-SVD transform) watermarks a host image before the watermark is extracted and decrypted at the receiver. As a contribution, our suggested approach introduces a new watermarking system based on discrete-time chaotic systems, as well as a hybridization of integer and fractional-order systems to ensure the watermarking scheme’s robustness. Our method achieved good results in terms of robustness, with normalized cross correlation values above 0.99 when subjected to a range of attacks. Results of the simulation underline practicality and robustness achieved by this approach. They also indicate that the proposed system resists various attacks.

Image Watermarking Using Discrete Wavelet Transform and Singular Value Decomposition for Enhanced Imperceptibility and Robustness

Digital multimedia elements such as text, image, audio, and video can be easily manipulated because of the rapid rise of multimedia technology, making data protection a prime concern. Hence, copyright protection, content authentication, and integrity verification are today’s new challenging issues. To address these issues, digital image watermarking techniques have been proposed by several researchers. Image watermarking can be conducted through several transformations, such as discrete wavelet transform (DWT), singular value decomposition (SVD), orthogonal matrix Q and upper triangular matrix R (QR) decomposition, and non-subsampled contourlet transform (NSCT). However, a single transformation cannot simultaneously satisfy all the design requirements of image watermarking, which makes a platform to design a hybrid invisible image watermarking technique in this work. The proposed work combines four-level (4L) DWT and two-level (2L) SVD. The Arnold map initially encrypts the watermark image, and 2L SVD is applied to it to extract the s components of the watermark image. A 4L DWT is applied to the host image to extract the LL sub-band, and then 2L SVD is applied to extract s components that are embedded into the host image to generate the watermarked image. The dynamic-sized watermark maintains a balanced visual impact and non-blind watermarking preserves the quality and integrity of the host image. We have evaluated the performance after applying several intentional and unintentional attacks and found high imperceptibility and improved robustness with enhanced security to the system than existing state-of-the-art methods.

Blind watermarking scheme for medical and non-medical images copyright protection using the QZ algorithm

The widely used watermarking technique is to hide the watermark information through adding process, which means the watermark is added with the host image to realize embedding. The constraints of these addition-based watermarking systems mainly are non-blind, they are vulnerable to forgery attacks and have the false-positive problem. To solve these problems, a novel blind watermarking scheme based on the QZ algorithm for medical and normal images is first presented in this paper. In the presented scheme, we take the watermark and the host image as two inputs of the QZ algorithm to realize embedding, rather than the adding process. The outputs of the QZ algorithm include four parts: two upper quasitriangular matrices and two unitary matrices. Then the three parts of the outputs are synthesized by the vector synthesis and inverse discrete wavelet transform-singular value decomposition (DWT-SVD) to obtain the watermarked host image. Due to the characteristics of the QZ algorithm, our scheme is blind. The performance is tested and compared by applying our scheme to both medical and non-medical images. The experimental results show that our scheme is robust against various image-processing attacks, forgery attacks, and false-positive problem. And from the comparison results, the proposed scheme outperforms the existing addition-based schemes in terms of robustness against the Median filter, Low-pass filter, Gaussian blur attacks, and forgery attacks, while maintaining good invisibility.

Region-Based Hybrid Medical Image Watermarking Scheme for Robust and Secured Transmission in IoMT

With the growth in Internet and digital technology, Internet of Medical Things (IoMT) and Telemedicine have become buzzwords in healthcare. A large number of medical images and information is shared through a public network in these applications. This paper proposes a region-based hybrid Medical Image Watermarking (MIW) scheme to ensure the authenticity, authorization, integrity, and confidentiality of the medical images transmitted through a public network in IoMT. In the proposed scheme, medical images are partitioned into Region of Interest (RoI) and Region of Non-Interest (RoNI). To ascertain integrity of RoI, tamper detection and recovery bits are embedded in RoI in the medical image. RoI is watermarked using adaptive Least Significant Bit (LSB) substitution with respect to the hiding capacity map for higher RoI imperceptibility and accuracy in tamper detection and recovery. Electronic Patient Record (EPR) is compressed using Huffman coding and encrypted using a pseudo-random key (secret key) to provide higher confidentiality and payload. QR code of hospital logo, Encrypted EPR, and RoI recovery bits are interleaved in RoNI using Discrete Wavelet Transform-Singular Value Decomposition (DWT-SVD) hybrid transforms to achieve a robust watermark. The proposed scheme is tested under various geometric and non-geometric attacks such as filtering, compression, rotation, salt and pepper noise and shearing. The evaluation results demonstrate that the proposed scheme has high imperceptibility, robustness, security, payload, tamper detection, and recovery accuracy under image processing attacks. Therefore, the proposed scheme can be used in the transmission of medical images and EPR in IoMT. Relevance of the proposed scheme is established by its superior performance in comparison to some of the popular existing schemes.

Effect of ZnO nanoparticles on optical textures and image analysis properties of 7O.O5 liquid crystalline compound

Abstract The systematic studies are carried out on liquid crystalline N-(p-n-heptyloxybenzylidene)-p-n-pentyloxy aniline (7O.O5) pure compound and with dispersion of ZnO nanoparticles in 1 wt% respectively. The phase transition studies of the pure and LC nanocomposite are carried out using Polarizing Optical Microscope (POM) attached with hot stage along with digital camera and Differential Scanning Calorimetry (DSC) is used to measure enthalpy and transition temperature values. Further the presence of ZnO nano particles in 7O.O5 is determined by Scanning Electron Microscopy (SEM) analysis. It is identified that due to dispersion of nano particles SmG phase is Quenched and nematic thermal range is increased. To enhance the captured textural images, an algorithm that uses tuned intensification operators have been proposed in this article. Statistical parameters for enhanced output images are calculated and compared with existing algorithms such as Adaptive Gamma Correction (AGC) and Discrete Wavelet Transform – Singular Value Decomposition (DWT-SVD) to understand the effectiveness of proposed algorithm. Further, optical parameters have been computed to understand the thermo optical nature of liquid crystalline compounds.

An Efficient Watermarking Approach Based on LL and HH Edges of DWT-SVD.

Digital watermarking is playing a vital role in the improvement of authentication, security, and copyright protection in today’s digital transformation. The performance of this technique is shown to be impressive around the globe. Text, audio, video, and image data are acted as watermarks in the digital platform. In this article, a hybrid watermarking scheme is proposed to furnish the robustness and protection of digital data. This hybrid scheme is a form of discrete wavelet transform (DWT) and singular value decomposition (SVD). The embedding and extracting features are carried out through multi-level operations of DWT and SVD. Various attacks are added to the proposed method to justify the robustness of the watermark. In the end, the suggested approach is contrasted with existing methods to confirm the supremacy.

Digital watermarking with improved SMS applied for QR code

With the rapid development of information technology, infringements have become increasingly serious. Digital watermarking is an effective method to protect information. The current watermarking technology still has room for further improvement in imperceptibility and robustness. This paper proposes an improved watermarking technology using meta-heuristic algorithm. Further, Quick Response code (QR code) is used as a carrier to transmit information. The improved Discrete Wavelet Transform-Singular Value Decomposition (DWT-SVD) is used to hide the watermark into the QR code. Therefore, digital watermarking is realized on the QR code. In the common watermark embedding methods, the digital watermark is related to the embedding strength. How to find a suitable embedding factor and reduce distortion is of great significance to these watermarking algorithms. This paper mainly proposes two novel algorithms based on States of Matter Search (SMS) algorithm to find suitable embedding factors. The first algorithm uses an adaptive parameter to control the movement of particles called the adaptive step States of Matter Search (sSMS). The second algorithm incorporates co-evolutionary matrix to enhance the search capability named Co-evolution States of Matter Search (CSMS). DWT-SVD is updated through two algorithms to acquire optimal embedding strength factors on the QR code watermarking. By adjusting the embedding strength factors, the intensity of the watermark embedded in different frequency domains would be modified. The experimental results have higher PSNR and the QR code can still be decoded by a general decoder. It shows that the proposed approaches are practicable and effective.

An enhanced hybrid image watermarking scheme for security of medical and non-medical images based on DWT and 2-D SVD

In this paper, we proposed a blind image watermarking scheme to enhance the effectiveness of hybrid Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) based schemes using the second level of SVD. The foremost contribution of this paper is to eliminate the constraints of our previous proposed scheme based on DWT and 2-level SVD. In the previous scheme, the size of the watermark was dependent to the size of cover image. For example, for a cover image with the size of 512*512, the watermark should be changed to 64*64 because of the limitation in capacity. In the proposed scheme, we enhanced the scheme to be independent from the sizes of cover and watermark images as well as improving the robustness and imperceptibility. For this purpose, we presented image blocking to find optimum block size for embedding the watermark and to correct the enslavement of capacity with the host image size. To achieve these goals, an additional preprocessing is performed on the watermark image before watermark embedding. The watermark image will be duplicated redundantly to the size of the cover image. Then both cover and watermark images will be divided into non overlap 16*16 blocks. Also, security is ensured in this scheme by proposing a two-level authentication system for watermark extraction to detect both false positive and false negative problems. The proposed scheme is tested and certified for medical and non-medical images exposing on 10 types of signal processing and geometric attacks. Experimental result shows, significant enhancement in both imperceptibility and robustness with the average of 46.9496 db and more than 99% respectively, while image blocking makes the capacity independent from the size of the host image.

A novel approach for liver image classification: PH-C-ELM

Classification of liver masses is one of the hot topics in the literature. This paper proposes a hybrid method of using Convolutional Neural Network (CNN) and Discrete Wavelet Transform- Singular Value Decomposition (DWT-SVD) based perceptual hash function. The aim of the proposed method is to reduce the execution time of CNN architecture, space of liver images occupied on the hard disk and maintain the classification performance above an acceptable threshold. The proposed method has been designed for classifying malignant and benign masses from liver CT images. The most important features required for classification are achieved by the acquisition of salient features using Perceptual hash functions. Experimental evaluation was performed with 5-fold cross validation on a set of 200 CT images, 100 of benign tumors and 100 of malignant tumors. Results showed that the CNN features achieved high classification performance with different classifiers. However, experimental results show that CNN features achieved better classification performance with ELM, where ELM simulation results validated output data with success 97.3%.

Robust watermarking in DWT domain using SVD and opposition and dimensional based modified firefly algorithm

The process of authenticating a digital image by embedding a watermark into it is called digital image watermarking, which protects the image from copyright infringement. This paper proposes an optimized watermarking scheme in the discrete wavelet transform (DWT) domain based on the singular value decomposition (SVD) using opposition and dimensional based modified firefly algorithm (ODFA).The host image is segmented into 8 × 8 non-overlapping blocks and the most suitable embedding blocks are selected for embedding. The selected blocks are then transformed into DWT domain and SVD is applied on LL1 sub-bands. Finally, the process of embedding the watermarked bits is optimized using ODFA, which applies the combination of imperceptibility and robustness as the objective function. The embedding algorithm possesses good similarity between the host and the watermarked images as well as the strong robustness against various image processing operations and attacks. Experimental results reveal that the proposed scheme has a higher degree of imperceptibility and robustness compare to related existing schemes.

CT scan contrast enhancement using singular value decomposition and adaptive gamma correction

We propose in this paper a new enhancement algorithm dedicated to dark computed tomography (CT) scan based on discrete wavelet transform with singular value decomposition (DWT–SVD) followed by adaptive gamma correction (AGC). Discrete wavelet transform (DWT) is considered to decompose the input dark CT image in four sub-bands. Singular value decomposition (SVD) is used in order to compute the corresponding singular value matrix of low–low (LL) sub-band image. The enhanced LL sub-band is determined by scaling the singular value matrix of original LL sub-band by an adequate correction factor, followed by inverse SVD. For a further contrast improvement, the new enhanced LL sub-band image is processed using an AGC algorithm. Finally, the obtained LL sub-band image undergoes inverse DWT together with the unprocessed sub-bands to generate the final enhanced image. This proposed method has the advantage of being fully automatic and could be applied for dark input images with either low or moderate contrast. Different dark CT images are considered to compare the performance of our proposed method to three other enhancement techniques using both objective and subjective assessments. Simulation results show that our proposed algorithm consistently produces good contrast enhancement, with best brightness and edges details conservation and with minimum added distortions to the enhanced CT images.

Linear weighted watermarking using normalized principal components

This manuscript introduces a novel linear weighted watermarking through normalized principal components using discrete wavelet transform (DWT) and singular value decomposition (SVD). Weight evaluation for embedding a singular value matrix of a watermark into a host is a trivial task in watermark embedding process. This task is accomplished by the normalized principal components derived from the singular value matrices of HH subbands of the host and the watermark images. Experiments are conducted to analyze the effectiveness of the proposed watermark embedding and watermark-host extraction processes against the other DWT–SVD based watermarking schemes. Performance of this method is analyzed by peak signal to noise ratio, structural similarity index and correlation coefficient. The proposed method is also tested against various geometrical and non-geometrical attacks on watermarked images.

DWT–SVD–WHT Watermarking Using Varying Strength Factor Derived From Means of the WHT Coefficients

A hybrid, watermarking technique is presented in this paper. This robust watermarking technique uses discrete wavelet transform (DWT), singular value decomposition (SVD) and Walsh–Hadamard transform (WHT) together in tandem with each other. There are two novelties contained in this paper. First is the combined use of DWT, SVD and WHT, and second is the first ever use of the $$4\times 4$$ block segmentation in the robust watermarking. Another unique feature of the presented technique is that visual quality of the watermarked image has been made controllable. A varying valued strength factor having a different value for every block ( $$8\times 8$$ or $$4\times 4$$ ) of the image has been used. Proposed scheme is very secure as the safety of the embedded watermark is not compromised even if there is an interception of the side information. The proposed technique shows remarkable performance when compared with seven contemporary watermarking schemes.

Digital Speech Watermarking Based on Linear Predictive Analysis and Singular Value Decomposition

In this paper different digital audio watermarking techniques have been proposed. Currently, more attention is given to combination of Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) techniques for watermarking purpose. Available DWT–SVD audio watermarking techniques cannot be applied to speech signals efficiently. However, Linear Predictive Analysis (LPA) technique can model digital speech signals (20–30 ms) in more flexible and efficient ways than DWT. In this paper, a novel digital speech watermarking technique is proposed by applying both LPA and SVD. Quantization Index Modulation (QIM) is further applied to embed the watermark bits. The experimental results show that not only time and memory were reduced significantly as compared to different DWT–SVD audio watermarking techniques, but also the proposed technique was more robust and imperceptible for speech watermarking than other DWT–SVD audio watermarking techniques.

Comparative Analysis of Color Image Watermarking Technique in RGB, YUV, and YCbCr Color Channels

Since there are a number of color spaces, it has always been a big question to choose one for watermarking. The aim of this work is to find out better color space, among the frequently used one, under the same condition. Comparative performance analysis of color image watermarking technique in color channels of RGB, YUV, YCbCrcolor spaces was studied. For this purpose, color channels were watermarked using single level discrete wavelet transform-singular value decomposition (DWT-SVD). PSNR, and SSIM were used to test the imperceptibility of watermarked images. PSNR and NCC were used to measure the similarity of extracted and original watermarks.The maximum recorded PSNR value is 62.372 for R channel of RGB color space with SSIM value equal to 0.9709. Color channels of YCbCr color space were observed to be more robust and transparent as watermark image is best recovered from YCbCr color space with NCC values in the range 0.86 to 0.877 and SSIM values in the range 0.546to 0.554 under various geometric attacks.DOI: http://dx.doi.org/njst.v15i2.12130Nepal Journal of Science and Technology Vol. 15, No.2 (2014) 133-140

A highly secure oblivious sparse coding-based watermarking system for ownership verification

In the last few decades, the watermarking security issue has become one of the main challenges facing the design of watermarking techniques. In this paper, a secure oblivious watermarking system, based on Sparse Coding (SC) is proposed in order to tackle the three most critical watermarking security problems, i.e., unauthorized reading, false positive detection, and multiple claims of ownership problems, as well as optimize the fidelity, imperceptibility, and robustness characteristics. The reason for incorporating SC in the proposed system is to encode the watermark image before embedding it in the host image. This process is implemented using the well-known Stagewise Orthogonal Matching Pursuit (StOMP) method and an orthogonal dictionary that is derived from the host image itself. The watermark embedding is implemented in the transform domain of the Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) of the host image. The proposed system is oblivious, as it does not need the original host image when extracting the embedded watermark. In addition, it is suitable for both bi-level and gray-level watermarks, and can accommodate large watermarks that are up to half the size of the host image. The proposed SC–DWT–SVD based watermarking scheme is tested for various malicious and un-malicious attacks and the experimental results show that it realizes the security requirement as it tackles the false positive detection and multiple claims of ownership problems on one hand and generates an encryption form of the watermark on the other hand. In addition, the added security does not compromise the imperceptibility and robustness aspects of the proposed technique and hence can be considered to be comparable or superior to other up-to-date watermarking techniques.

Exploring DWT–SVD–DCT feature parameters for robust multiple watermarking against JPEG and JPEG2000 compression

This paper presents a novel scheme to implement blind image watermarking based on the feature parameters extracted from a composite domain including the discrete wavelet transform (DWT), singular value decomposition (SVD), and discrete cosine transform (DCT). Multiple bits can be embedded into a single image block by adjusting designated parameters via a progressive quantization index modulation technique. The quantization with respect to the feature parameters obtained in the DWT–SVD–DCT domain leads to efficient watermark extraction without referring to the original image. Experimental results show that the embedded watermarks exhibit exceptional robustness against image compression using JPEG and JPEG2000 coding standards.

Optimized gray-scale image watermarking using DWT–SVD and Firefly Algorithm

This paper presents an optimized watermarking scheme based on the discrete wavelet transform (DWT) and singular value decomposition (SVD). The singular values of a binary watermark are embedded in singular values of the LL3 sub-band coefficients of the host image by making use of multiple scaling factors (MSFs). The MSFs are optimized using a newly proposed Firefly Algorithm having an objective function which is a linear combination of imperceptibility and robustness. The PSNR values indicate that the visual quality of the signed and attacked images is good. The embedding algorithm is robust against common image processing operations. It is concluded that the embedding and extraction of the proposed algorithm is well optimized, robust and show an improvement over other similar reported methods.

A Digital Image Watermarking Algorithm Based on DWT DCT and SVD

 Abstract—Digital watermarking techniques have been developed to protect the copyright of multimedia objects such as text, audio, video, etc. In this paper, we propose a new digital watermarking algorithm with gray image based on discrete wavelet transform (DWT), 2 dimensions discrete cosine transform (DCT) and singular value decomposition (SVD) for robust watermarking of digital images in order to protect digital media copyright efficiently. One of the major advantages of the proposed scheme is the robustness of the technique on wide set of attacks. Experimental results confirm that the proposed scheme provides good image quality of watermarked images. Index Terms—Digital image watermarking, DWT, DCT PSNR, SVD.

Differential evolution algorithm for the selection of optimal scaling factors in image watermarking

In this paper, an innovative watermarking scheme based on differential evolution (DE) in the transform domain is proposed. The insertion and extraction of the watermark are performed in discrete wavelet transform-singular value decomposition (DWT–SVD) transform domain. In the embedding process, the host image is transformed into sub-bands of different frequencies by third-level DWT and then subsequent application of SVD on low pass (LL) and high pass (HH) sub-bands at level third. The watermark image is properly scaled down by multiplying with different scaling factors (SFs) and embedded in the Singular value matrix of LL and HH sub-bands of the host image to make the watermark invisible and robust. We applied an optimization technique, differential evolution, to search optimal scaling factors to improve the quality of watermarked image and robustness of the watermark. In order to overcome the false positive problem, a binary watermark is also embedded in the host image in a lossless manner. According to the numerical results, the quality of watermarked image is satisfactory and embedded watermark is extracted successfully even if the watermarked image is exposed to various image processing and geometric attacks.