Comparative Study of DCT and DWT Techniques of Digital Image Watermarking

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

Nowadays, the development of technology which involves multimedia data is widely used to help better understanding in spreading information. Image is known as 2D signal which contain huge data especially a high resolution image. This paper shows the comparison of applying lossy and lossless compression on the image data. Image compression is necessary in reducing the size of image for storage or transmission purpose to support most of the application nowadays. The technique applied in this paper is the hybrid of Discrete Wavelet Transform (DWT) technique and Huffman coding technique which are classified as lossy and lossless compression, respectively. The performance of image compression are evaluated in terms of compression ratio, Mean Square Error (MSE), Power Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM) and computing time. Several types of evaluation can determine better technique to apply on specific type of application. The stand-alone of each DWT and Huffman technique are evaluated before applying hybrid of DWT and Huffman technique. After conducting a comprehensive observation, the hybrid technique can compress with ratio about 1:17 to 1:27 due to the support from DWT technique that apply filter concept. The MSE value is high with the average about 69 which contributes to low PSNR value with about 29 to 30 dB due to the relation of PSNR equation with MSE value. Besides, the SSIM value is 0.6 or about 40% far from the original image that affect the output image. Despite of that, the computing time is fast with about 3 to 4 seconds which has been improved from stand-alone Huffman technique. Therefore, hybrid compression is capable of supporting each other techniques in stand-alone technique.

In this paper, a robust algorithm of digital image watermarking based on discrete wavelet transform is introduced It uses blind watermarking technique. Digital image watermarking is one such technology that has been developed to protect digital images from illegal manipulations. In particular, digital image watermarking algorithms which are based on the discrete wavelet transform have been widely recognized to be more prevalent than others. This is due to the wavelets' excellent spatial localization, frequency spread, and multi-resolution characteristics, which are similar to the theoretical models of the human visual system.

-- Digital watermarking plays a critical role in ensuring the protection, authenticity, and integrity of multimedia content, particularly in today's data-driven environment. In this paper, we present a solution for the watermarking of grayscale images utilizing the Discrete Wavelet Transform (DWT) technique. Our approach focuses on embedding watermark information into the frequency components of the image to achieve a balance between imperceptibility and robustness against common signal processing attacks. A complete software-based implementation of the watermark embedding and extraction process has been developed and evaluated using standard grayscale images. Additionally, we propose a high-level VLSI architecture for real-time implementation of the DWT-based watermarking system, emphasizing efficient resource utilization, parallelism, and low power design. Extensive simulations demonstrate the effectiveness of the DWT-based watermarking method, achieving strong imperceptibility and resilience. This research contributes to the growing field of digital image security by presenting a practical approach to scalable hardware design and opens new directions for future real-time, hardware-accelerated watermarking applications. Key Words: Digital watermarking, Discrete Wavelet Transform (DWT), Grayscale images, VLSI architecture, Image security, Frequency domain, Robustness, Imperceptibility, Hardware design, Real-time systems.

Today, most of the information shared across the globe is in multimedia form like audio, video and image. With increased globalization, any type of such information can be broadcasted throughout the world easily and is accessible to multiple users for varied applications. This may lead to fraudulent claiming of data ownership which makes copyright protection a major priority in today's world. Digital Watermarking serves as a prime solution to copyright protection where we embed watermark into digital image which serves as an authenticator. In this paper, we proposed a hybrid algorithm using Image segmentation, SVD (Singular value decomposition), DWT (Discrete wavelet transformation), Homomorphic filtering and RSA encryption technique that helps to overcome various threats. Here, we proposed a new approach of digital watermarking by embedding two segmented watermarks which are obtained using two distinct threshold values on the original watermark. These threshold values are sent as secret keys to the receiver using Diffie-Hellman key exchange algorithm and can be used at the time of copyright verification. This approach of hybrid technique is being tested by applying Gaussian Noise and it gave the best results when compared with the other digital watermarking techniques.

Human heart cardiac muscles activities can be represented graphically using electrical impulses. Electrocardiography (ECG) signals are very important for physicians to diagnose heart disease. In this study, Bluetooth device is used to transmit data wirelessly. For this purpose, the generated signal from heart beat sensor is analyzed in MATLAB using Support Vector Machine (SVM) and Discrete Wavelet Transform (DWT) techniques. ECG Simulator compares the actual signal of infants with the reference signal and notify the physician about healthy or unhealthy ECG signals. Additionally, simulating the ECG pattern of different infants before designing and developing any biomedical technology is quite efficient and cost-effective.

We propose in this paper a discrete wavelet transform (DWT) based digital image watermarking technique. For embedding process, we consider the watermark signal as a binary sequence which is embedded to the high (HL and HH) frequency band of the blue channel. For detecting process, the correlation between the high frequency band DWT coefficients of the watermarked image and the watermark signal is compared with the predefined threshold to determine whether the watermark is present or not. The experimental results show that the method is comparatively robust to several attacks such as rotation, scaling, JPEG compression, cropping, and multiple watermarking.

Two digital image watermarking techniques that have higher level of security compared to most of the existing algorithms have been proposed. The proposed digital watermarking scheme uses the properties of Discrete Cosine Transform (DCT) and Discrete Wavelet Transforms (DWT) to achieve almost zero visible distortion in the watermarked images. These techniques use a unique method for spreading, embedding and extracting the watermark. Embedding using a linear relation between the transform coefficients of the watermark and a security matrix has been proposed with satisfactory results. It has been shown that instead of adding the watermark to the source image, as is normally done, multiplying the watermark with the transformed source could be a preferred technique, as it would retain the original bit rate to a large extent. The watermarked images were tested subject to image cropping.

An Invisible Logo Watermarking Using Arnold Transform

HVS theory plays important role in the application of digital image watermarking technique. When inserting watermarking, the visual masking feature of HVS could be fully used to design digital watermarking algorithm with good perceived performance. When extracting watermarking from the damaged image, human's visual feature could be combined to recover the damaged image so as to obtain better effect. This article combines with human visual feature to study digital watermarking technique, utilizes watermarking redundant technique to insert watermarking, extracts watermarking in line with the damage situation of watermarking, and combines with visual redundancy feature to achieve a image scrambling algorithm that is easy to recover and a recovery scheme for damaged scrambling image.

This chapter extensively delves into the realm of digital image watermarking, encompassing comparisons with analogous information security methodologies, elucidations of watermark embedding and extraction procedures, discussions on watermark attributes and applications, overviews of prevalent watermarking tactics, and a concise recapitulation of secure watermarking approaches. The primary focus of this discourse lies in advanced strategies for shielding healthcare data using digital watermarking techniques, with special emphasis on the integration of discrete wavelet transform (DWT), discrete cosine transform (DCT), and singular value decomposition (SVD). Recognizing the inherent challenges in safeguarding medical data amidst the dynamic healthcare landscape, the investigation explores multifaceted watermarking algorithms. Leveraging foundational principles from DWT, DCT, and SVD, the study amalgamates prior research and provides comparative evaluations of the efficacy of these methodologies through tabular representations.

Zernike Moments (ZMs) are used in many image processing applications, due to their resistance against various signal processing and geometric attacks. Digital image watermarking is one of those application areas, where ZMs are widely used to insert and extract the watermark bits for digital media authentication. In all the existing ZM based watermarking techniques, magnitude of moments is used to insert and extract the watermark. In this paper, the authors’ have proposed a semi blind watermarking technique in which phase of ZMs is used for watermark insertion and extraction. Due to the use of phase of ZMs, 100% detection ratio is achieved against any geometric and other signal processing attacks. To make the proposed technique fast, q-recursive method is used to compute the Zernike polynomials. The use of q-recursive method has also increased the transparency of watermark due to its better reconstruction ability as compared to traditional moment computation method. Through detailed experimentation, it has been confirmed that the proposed watermarking technique is fast, has more imperceptibility, less Bit Error Rate (BER) and more capacity as compared to traditional ZMs magnitude based watermarking technique.

In this paper, we propose a digital image watermarking scheme using Arnold transform. To implement this, a scrambled binary image is embedded into the coefficient of host images via Lifting wavelet transform. Then inverse wavelet transform is applied to get the watermarked image. We have applied to watermark in the transform domain instead of the spatial domain. This is since in a spatial domain the pixels of the cover image is directly manipulated, in contrast with transform domain where the coefficient of pixels is modified after applying different transformation technique that ultimately increases imperceptibility of the scheme. Moreover, nowadays most of the images are compressed in wavelet domain like JPEG 2000. Another important feature of the proposed algorithm is the Arnold scrambling technique which increases the security of the scheme. It is difficult for the attacker to derive the original watermark as well as retrieve the cover image. The proposed digital watermarking system is tested over a large number of standard grayscale (512×512) benchmark images to provide good imperceptibility and robustness. In our case, we have seen that the proposed technique offers the average value of peak signal-to-noise ratio (PSNR), Structural Similarity Index (SSI) before decoding and after decoding are 49.93, 0.97, 51.72 and 0.976721 respectively. The experimental results show that the proposed scheme is robust against different types of attacks.

The success of internet technology transform the world of technology and fashioned our life such a lot easier. The matter of duplication and unauthorized use of information become a great threat within the field of technology. To beat these problems, techniques like digital watermarking, steganography and cryptography were introduced. The approach of embedding a secret data associated with the digital signal inside the signal itself is digital watermarking. For embedding and detecting the watermark different techniques are used; spatial domain techniques like Least Significant Bit (LSB) and Patch Work Algorithm, then the frequency domain techniques such as Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) and Discrete Fourier Transform (DFT) are some of them. Combination of DCT & DWT technique for digital watermarking is proposed here. The proposed methodology is implemented in MATLAB 2017a simulator and result is analysed using evaluation parameters like Peak Signal to Noise Ratio (PSNR) & Mean Square Error (MSE). PSNR value obtained for the case of watermarking using DWT is 27.46 and MSE value is 17.45. The value of PSNR for watermarking using DCT is 41.4 and for MSE the value is 0.67. The PSNR and MSE values obtained for watermarking using LSB technique is 50.55 and 0.58. The proposed method improves the watermarked image quality and the MSE & PSNR value obtained is 0.52 and 51.017 respectively.

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.