Improved hybrid algorithm for robust and imperceptible multiple watermarking using digital images

In this paper, a blind image watermarking scheme based on discrete wavelet transform (DWT) and singular value decomposition (SVD) is proposed. In this scheme, DWT is applied on ROI (region of interest) of the medical image to get different frequency subbands of its wavelet decomposition. On the low frequency subband LL of the ROI, block-SVD is applied to get different singular matrices. A pair of elements with similar values is identified from the left singular value matrix of these selected blocks. The values of these pairs are modified using certain threshold to embed a bit of watermark content. Appropriate threshold is chosen to achieve the imperceptibility and robustness of medical image and watermark contents respectively. For authentication and identification of original medical image, one watermark image (logo) and other text watermark have been used. The watermark image provides authentication whereas the text data represents electronic patient record (EPR) for identification. At receiving end, blind recovery of both watermark contents is performed by a similar comparison scheme used during the embedding process. The proposed algorithm is applied on various groups of medical images like X-ray, CT scan and mammography. This scheme offers better visibility of watermarked image and recovery of watermark content due to DWT-SVD combination. Moreover, use of Hamming error correcting code (ECC) on EPR text bits reduces the BER and thus provides better recovery of EPR. The performance of proposed algorithm with EPR data coding by Hamming code is compared with the BCH error correcting code and it is found that later one perform better. A result analysis shows that imperceptibility of watermarked image is better as PSNR is above 43 dB and WPSNR is above 52 dB for all set of images. In addition, robustness of the scheme is better than existing scheme for similar set of medical images in terms of normalized correlation coefficient (NCC) and bit-error-rate (BER). An analysis is also carried out to verify the performance of the proposed scheme for different size of watermark contents (image and EPR data). It is observed from analysis that the proposed scheme is also appropriate for watermarking of color image. Using proposed scheme, watermark contents are extracted successfully under various noise attacks like JPEG compression, filtering, Gaussian noise, Salt and pepper noise, cropping, filtering and rotation. Performance comparison of proposed scheme with existing schemes shows proposed scheme has better robustness against different types of attacks. Moreover, the proposed scheme is also robust under set of benchmark attacks known as checkmark attacks.

Telemedicine is well known application where enormous amount of medical data need to be transferred securely over network and manipulate effectively. Security of digital data, especially medical images, becomes important for many reasons such as confidentiality, authentication and integrity. Digital watermarking has emerged as a advanced technology to enhance the security of digital images. The insertion of watermark in medical images can authenticate it and guarantee its integrity. The watermark must be generally hidden does not affect the quality of the medical image. In this paper, we propose blind watermarking based on Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD), we compare the performance of this technique with watermarking based DWT and SVD. The proposed method DWT, DCT and SVD comparatively better than DWT and SVD method.

Due to the development of the latest technologies in the areas of communication and networking, the present businesses are moving to the digital world for accuracy, accessibility, safety and security. Normally, the medical image requires additional care to handle because treatment is mainly focused on the detail received from the medical images. Nowadays, digital watermarking is a blooming methodology for protecting medical data as for as security is concerned. This proposed method gives a new watermarking scheme for a secure transfer of Electronic Patient Record (EPR) using Hybrid Transform (DWT+DCT+SVD). Initially, the medical image is decomposed by Discrete Wavelet Transform then after Discrete Cosine Transform is performed in LH band and then Singular Value Decomposition is performed and a similar process to be done for the watermark image for embedding process and perform an inverse process for obtaining the watermarked image. Similarly, the above process to be done for the extraction process on the watermarked image to exact the EPR data and medical image. The effectiveness and performance of the proposed watermarking scheme being analyzed by measuring Peak Signal to Noise Ratio (PSNR) and Quality Index. The result is discussed with the help of experimental results using MATLAB tools.

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.

This chapter presents an improved robust and imperceptible hybrid watermarking technique for medical images using fusion of DWT, DCT and SVD instead of applying DWT, DCT and SVD individually or combination of DWT-DCT, DWT-SVD, and DCT-SVD. In the embedding process, the host image is decomposed into first level discrete wavelet transforms where the low frequency band (LL) is transformed by DCT and SVD. The watermark image is also transformed by DCT and SVD. The ‘S’ vector of watermark information is embedded in the ‘S’ component of the host image. The watermarked image is generated by inverse SVD on modified ‘S’ vector and original U, V vectors followed by inverse DCT and inverse DWT. The watermark is extracted using an extraction algorithm. The performance of proposed technique is also tested by using the benchmark software 'Checkmark' and the technique is found to be robust against the 'Checkmark' attacks. Moreover, the performance of proposed algorithm has also been evaluated for multiple watermarking. The proposed multiple watermarking method preventing the problem of patient identity theft and health data management issues in the healthcare applications.

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 paper proposes the enhancement of low contrast satellite images based on intensity transformation. The intensity transformation is achieved using gamma correction on discrete wavelet transform (DWT) and the better illumination is achieved by singular value decomposition (SVD) technique. The DWT decomposes the input image in four different frequency sub-bands; low-low (LL), low-high (LH), high-low (HL) and high-high (HH). The gamma correction is applied only on LL sub-band to preserve the edge information. To improve the illumination, these gamma corrected LL sub-band information are passed through SVD. The enhanced image obtained is reconstructed by taking inverse discrete wavelet transform (IDWT). The performance measure is carried out in terms of EME, entropy and signals to noise ratio.

Nowadays image authentication plays a vital role for security. Watermarking techniques facilitate to hide the data in carrier image in such a way so that data would become imperceptible. Watermarking can be performed either in spatial domain or in transfer domain. Least Significant Bit (LSB) modification is the simple but non reliable theme, which is performed in spatial domain. In transfer domain, Singular Value Decomposition (SVD), Discrete Cosine Transformation (DCT), Fast Fourier Transformation (FFT), Discrete Wavelet Transformation (DWT) and Fast hadamard Transform (FHT) etc provide robust result. The goal of the paper is to present how such methods are useful to authenticate images and avoid image tampering. In our work, we have discussed block and non block based watermarking scheme performed in DCT domain using SVD. Several experiments are carried out to check the robustness of the algorithm. We conclude that non block based algorithm is superior in terms of visual quality after embedding and extraction, while its inferior in terms of some common signal processing attacks like rotation, scaling, translation etc.

This paper presents an audio watermarking scheme that ensures the efficient of robustness-distortion ratio and a pleasing amount of capacity. Quantization Index Modulation (QIM) method synergism along with Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), Singular Value Decomposition (SVD), and Cartesian to Polar Transformation (CPT) to emphasize copyright protection for harmonical work of art. DWT synergism along with DCT, SVD, and CPT to emphasize copyright protection for harmonical work of art. The system establishes with DWT that divides the signal within a specific range of frequency, alter it to the frequency domain by DCT, partite with mathematical processing SVD, and transform the peculiar value of matrix-S to polar value using CPT, furthermore, QIM embed the watermark into the angular value from the CPT. The system performance is astonishing, tested using 4 different audio host signal and evaluated considers to desirable Bit Error Rate (BER) <; 0.025, Signal-to-Noise Ratio (SNR)>21dB, a great amount of data payload that is 525 bit per second, and the noise caused by watermark is inaudible. All of the experiments, trials, and results show that the designed audio watermarking system is robust and imperceptible.

Image watermarking is a sophisticated method often used to assert ownership and ensure the integrity of digital images. This research aimed to propose and evaluate an advanced watermarking technique that utilizes a combination of singular value decomposition methodology and discrete cosine transformation to embed the Dian Nuswantoro University symbol as proof of ownership into digital images. Specific goals included optimizing the embedding process to ensure high fidelity of the embedded watermark and evaluating the fuzziness of the watermark to maintain the visual quality of the watermarked image. The methods used in this research were singular value decomposition and discrete cosine transformation, which are implemented because of their complementary strengths. Singular value decomposition offers robustness and stability, while discrete cosine transformation provides efficient frequency domain transformation, thereby increasing the overall effectiveness of the watermarking process. The results of this study showed the efficacy of the Lena image technique in gray scale having a mean square error of 0.0001, a high peak signal-to-noise ratio of 89.13 decibels (dB), a universal quality index of 0.9945, and a similarity index structural of 0.999. These findings confirmed that the proposed approach maintains image quality while providing watermarking resistance. In conclusion, this research contributed a new watermarking technique designed to verify institutional ownership in digital images, specifically benefiting Dian Nuswantoro University. It showed significant potential for wider application in digital rights management.

Digital watermarking is an emerging technique to protect data security and intellectual property right. Identification or verification of watermarking patterns can be achieved by detecting watermarks in received signals. However, one of the biggest challenges in watermarking detection is that the strengths of the watermark signals will change after being distorted by an attacker in a watermarking channel. Meanwhile, the embedding strengths may be adapted to the original signals, which are unknown at the receiver end. Further, the original signals are often highly non-Gaussian. Although some work has been done on optimum detection of watermarks, the uncertainty of watermark signal strengths and real statistical behavior of multimedia contents have not been taken into account simultaneously. Much more study is needed to enhance the performance of watermarking systems. Since multiplicative watermarks are robust and well suited for copyright protection, this paper presents our investigation on robust optimum detection of multiplicative watermarks. For sub-band transformed domains such as the discrete cosine transform (DCT), discrete wavelet transform (DWT), and pyramid transform, a class of generalized correlators is constructed based on the generalized Gaussian distributions. Thresholding methods to achieve a given false alarm rate, and the performance analyses are provided. The square-root detector is designed and demonstrated to have near performance for a large set of natural images and can be employed as a universally optimal detector or decoder for images and video. The locally most powerful detection method is then extended to DFT domain multiplicative watermarking, with the magnitudes of coefficients modeled by the Weibull distributions. Another class of detectors is built based on this statistical modeling. The robust optimum detection of multiplicative watermarks can be applied to copyright notification, enforcement, and broadcast monitoring. We have applied the robust optimum watermarking detection to combined audio and video watermarking.

In the field of image watermarking technology, it is very important to balance imperceptibility, robustness and embedding capacity. In order to solve this key problem, this paper proposes a new color image adaptive watermarking scheme based on discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD). In order to improve the security of the watermark, we use Lorenz hyperchaotic mapping to encrypt the watermark image. We adaptively determine the embedding factor by calculating the Bhattacharyya distance between the cover image and the watermark image, and combine the Alpha blending technique to embed the watermark image into the Y component of the YCbCr color space to enhance the imperceptibility of the algorithm. The experimental results show that the average PSNR of our scheme is 45.9382 dB, and the SSIM is 0.9986. Through a large number of experimental results and comparative analysis, it shows that the scheme has good imperceptibility and robustness, indicating that we have achieved a good balance between imperceptibility, robustness and embedding capacity.

This paper proposes a new illumination compensation technique based on iterative implementation of singular value equalization of low frequency subband of a given image. In this work, both input and reference images are decomposed into different frequency subbands by using discrete wavelet transform (DWT). Then low frequency subbands are used in order to compensate the illumination of the input image and achieve the same illumination of the reference image. Afterwards inverse DWT (IDWT) is used to reconstruct the illumination compensated image. The experimental results on various video resolution enhancement techniques show that maximum PSNR gain of 1.96 dB is achieved by applying the proposed illumination compensation technique.

The technique used to hide copyright information (watermark) into the digital audio signal is termed as audio watermarking. Audio watermarking is an excellent approach to provide a solution to mitigate challenges that occur from easy copying and distribution of audio files that are being downloaded or uploaded through the web. The audio watermarking algorithms proposed earlier were implemented by image or binary logo or a unique pattern as watermark. To tackle the difficulty of online musical piracy, unethical attempt to alter purposefully copyrighted audio data and unauthorized distribution and tampering of audio files an efficient audio watermarking method is suggested here. In this method the copyright information (watermark) which is an audio signal of shorter length is imperceptibly added into the original audio signal with greater duration. Here two audio watermarking methods using DCT (Discrete Cosine Transform) and then with DWT-SVD (Discrete Wavelet Transform — singular value decomposition) methods are proposed with audio signal encrypted with secure hash algorithm as watermark. A comparative study on performance evaluation of both DCT and DWT-SVD methods are made in terms of PSNR (Peak-Signal to Noise Ratio) and MSE (Mean Square Error). The results show that transparency is best for each methods and DWT-SVD method is more efficient against signal attacks. The elementary notion of this document is to provide a beneficial and satisfactory method for secure audio file transmission by providing copyright protection.

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