Algorithm In Transform Domain Research Articles

Adaptive decomposition with guided filtering and Laplacian pyramid-based image fusion method for medical applications

Medical image fusion enhances diagnostic precision and facilitates clinical decision-making by integrating information from multiple medical imaging modalities. However, this field is still challenging as the output integrated image, whether from spatial or transform domain algorithms, may suffer from drawbacks such as low contrast, blurring effect, noise, over smoothness, etc. Also, some existing novel works are restricted to specific image datasets. So, to address such issues, a new multi-modal medical image fusion approach based on the advantageous effects of multiple transforms has been introduced in the present work. For this, we use an adaptive image decomposition tool known as Hilbert vibration decomposition (HVD). HVD decomposes an image into different energy components, and after a proper decomposition of the source images, the desirable features of the decomposed components are then passed through a guided filter (GF) for edge preservation. Then, the Laplacian pyramid integrates these filtered parts using the choose max rule. Since HVD offers better spatial resolution and is independent of fixed cut-off frequencies like other transforms, the subjective outputs from this method for different publicly available medical image datasets are clear and better than the previously 20 state-of-the-art published results. Moreover, the obtained values of different objective evaluation metrics such as information entropy (IE): 7.6943, 5.9737, mean: 110.6453, 54.6346, standard deviation (SD): 85.5376, 61.8129, average gradient (AG): 109.2818, 64.6451, spatial frequency (SF): 0.1475, 0.1100, and edge metric (QHK/S): 0.5400, 0.6511 demonstrate its comparability to others. The algorithm's running period of just 0.161244 s also indicates high computational efficiency.

A Novel Video Copyright Protection Scheme Based on Blockchain and Double Watermarking

With the continuous development of multimedia, more and more digital works such as videos are spread, stored, and used in the network. In recent years, digital copyright infringement disputes have occurred frequently. The traditional copyright protection system has some problems, such as difficulty confirming copyright, monitoring infringement, and obtaining evidence for rights protection. To this end, we have designed and implemented a novel video copyright protection scheme based on the blockchain and double watermarking technology. We use the image correlation coefficient method to extract video keyframes. And we combine with Contourlet Transform domain, QR decomposition, and SIFT algorithm to improve the robustness of watermark against geometric attacks on the premise of invisibility. After that, we use Arnold Transformation (Cat Map) based on the Maximum Entropy Threshold Segmentation to encrypt the robust watermark and strengthen the security. Moreover, based on the characteristics of the fragile watermarking, we accurately locate the attacked video’s tamper position and complete the integrity authentication of the watermarked video. In addition, the hash digest of the video watermark and the user ID of the copyright owner is signed by SM2 and uploaded to the blockchain. The user can register the copyright after passing the identity authentication. We conduct tests and security analysis on the blockchain performance of the system, the performance of the commercial cryptography algorithm, and the security of the watermarking system. The experimental results show that the blockchain used in this system conforms to the industry standard, the performance of SM2 and SM3 is better than ECC-256 and SHA-256, and the system security is well guaranteed.

Robust and Blind Audio Watermarking Scheme Based on Genetic Algorithm in Dual Transform Domain

In order to protect the copyright of audio media in cyberspace, a robust and blind audio watermarking scheme based on the genetic algorithm (GA) is proposed in a dual transform domain. A formula for calculating the embedding depth is developed, and two embedding depths with different values are used to represent the “1” and “0” states of the binary watermark, respectively. In the extracting process, the embedding depth in each audio fragment will be calculated and compared with the average embedding depth to determine the watermark bit by bit, so this scheme can blindly extract the watermark without the original audio. GA will be applied to optimize the algorithm parameters for meeting the performance requirements in different applications. Besides, the embedding rule is further optimized to enhance the transparency based on the principle of minimal modification to the audio. Experimental results prove that the payload capacity reaches 172.27 bps, the bit error rate (BER) is 0.1% under the premise that its transparency is higher than 25 dB, and its robustness is strong against many attacks. Significantly, this scheme can adaptively select the algorithm parameters to satisfy the specific performance requirements.

Simulation of active noise control using transform domain adaptive filter algorithms linked with the inhomogeneous Helmholtz equation

An iterative approach is presented that couples the inhomogeneous Helmholtz equation with transform domain active noise control algorithms. The Boundary Element Method is utilized to provide solutions of the inhomogeneous Helmholtz equations for three dimensional pressure wave fields. The source terms in the inhomogeneous Helmholtz equations are adapted iteratively by the algorithm to achieve convergence in the noise cancelling process. The approach can be used to study the impact of active noise control systems based on transform domain algorithms on the wavefield for specific application environments. Additionally, this approach allows for numerical frequency-dependent performance evaluation of multichannel active noise control systems even in acoustically challenging environments. Ill-posed control problems can be identified. The required calculation steps for the integration of the method into existing numerical simulation environments are presented step by step. The study is supplemented by numerical experiments and convergence studies that show good agreement with acoustic theory and analytical results reported in literature.

A secure method in digital video watermarking with transform domain algorithms

One of the problems in the digital world is the secure transmission of information through insecure communication channels which has been selected as the main concept discussed in this research. This article, by thoroughly analyzing the types of attacks in video watermarking, learns the basics used in the proposed method and offers a solution to deal with the most important categories. Therefore, it presents a secure solution against collusion attacks by introducing a three-dimensional discrete cosine transform algorithm. According to the evaluations, it can be claimed that the proposed solution is resistant to collusion attacks, which is the most important attack in the field of digital watermarking. Another strength of the proposed algorithm compared to other methods is its higher capacity in watermarking. The proposed algorithm, using its special blocking method, has the ability to cover all types of video, both dynamic and static. Various tests have been applied to the selected dataset to analyze the security and the performance of the proposed algorithm. The results show that if the proposed algorithm is used in watermarking, in addition to high accuracy, it can have an acceptable resistance to attacks.

Digital media zero watermark copyright protection algorithm based on embedded intelligent edge computing detection.

With the rapid development of computer technology and network communication technology, copyright protection caused by widely spread digital media has become the focus of attention in various fields. For digital media watermarking technology research emerge in endlessly, but the results are not ideal. In order to better realize the copyright identification and protection, based on the embedded intelligent edge computing detection technology, this paper studies the zero watermark copyright protection algorithm of digital media. Firstly, this paper designs an embedded intelligent edge detection module based on Sobel operator, including image line buffer module, convolution calculation module and threshold processing module. Then, based on the embedded intelligent edge detection module, the Arnold transform of image scrambling technology is used to preprocess the watermark, and finally a zero watermark copyright protection algorithm is constructed. At the same time, the robustness of the proposed algorithm is tested. The image is subjected to different proportion of clipping and scaling attacks, different types of noise, sharpening and blur attacks, and the detection rate and signal-to-noise ratio of each algorithm are calculated respectively. The performance of the watermark image processed by this algorithm is evaluated subjectively and objectively. Experimental data show that the detection rate of our algorithm is the highest, which is 0.89. In scaling attack, the performance of our algorithm is slightly lower than that of Fourier transform domain algorithm, but it is better than the other two algorithms. The Signal to Noise Ratio of the algorithm is 36.854% in P6 multiplicative noise attack, 39.638% in P8 sharpening edge attack and 41.285% in fuzzy attack. This shows that the algorithm is robust to conventional attacks. The subjective evaluation of 33% and 39% of the images is 5 and 4. The mean values of signal to noise ratio, peak signal to noise ratio, mean square error and mean absolute difference are 20.56, 25.13, 37.03 and 27.64, respectively. This shows that the watermark image processed by this algorithm has high quality. Therefore, the digital media zero watermark copyright protection algorithm based on embedded intelligent edge computing detection is more robust, and its watermark invisibility is also very superior, which is worth promoting.

Transform Domain: Design of Closed-Form Joint 2-D DOA Estimation Based on QR Decomposition

As an alternative to existing methods, we design a transform-domain algorithm to avoid the computational cost of a two-dimensional (2-D) spectral peak search when addressing the problem of joint azimuth and elevation directions-of-arrival (DOAs) estimation via an L-shaped array. Motivated by the linear prediction property of the signal cross-covariance matrix, the 2-D DOA estimation problem is equivalently converted into a 2-D frequency estimation problem. With the QR decomposition technique, the closed-form solutions in the transform domain with respect to the azimuth and elevation angles are successively estimated using the weighted least squared method as the solver, and it is shown that the proposed scheme achieves automatically pairing while permitting fast implementation. Simulations are presented to verify the effectiveness of the proposed method by comparison with several 2-D DOA estimators as well as the Cramer–Rao lower bound.

Application of IIR Digital Filter with A New LMS Adaptive Algorithm

Any system will be inevitably disturbed by noise. The existence of noise affects the processing and application of real signals. How to effectively suppress and eliminate noise has always been a hot spot in the industrial field. In order to design a filter which can properly adjust its parameters according to different environments to obtain the optimal value, this paper designs an adaptive IIR digital filter, and studies as well as improves the adaptive algorithm. A new variable step size LMS algorithm based on multi-scale wavelet transform is proposed in this paper. The wavelet transform domain algorithm belongs to LMS transform domain algorithm and is a new time-frequency analysis method developed, so it has the characteristics of multi-resolution analysis. This adaptive IIR filter designed is applied to suppression and cancellation of noise, and simulation experiments are performed on the MATLAB software platform, so that better illustrating the superiority of this improved algorithm.

Content Based Image Retrieval using Transform Domain Features and Algorithms

In this paper, Content Based Image Retrieval using Transform domain features and algorithms has been implemented. The image can be decomposed by Discrete Wavelet Transform (DWT) to extract the features based on DC coefficients. Each sub-image is calculated by mean, variance and standard deviation to get more efficient recognition. The database image also applied in the domain of Stationary Wavelet Transform (SWT) and Integer Wavelet Transform (IWT) by using different distance measures. The proposed algorithm is the combination of DWT, SWT and IWT has been implemented using COREL database. This proposed method has more efficient recognition and less computational time over existing methods

A performance evaluation of transform domain algorithm in watermarking based on different levels of sub-bands of discrete wavelet transform

This study proposed to evaluate the performance of transform domain algorithms in watermarking based on different level of sub bands of discrete wavelet transform (DWT) that can be used to overcome illegal copy, manipulation, distribution and reproduction of image on the network by implementing watermarking algorithm based on different levels that is low-level (LL), low- high (LH), high-low (HL), High-high (HH) and singular value decomposition (SVD) on image for their robustness, and imperceptibility. Moreover, two parameters were applied to evaluate the performance. That is, peak signal to noise ratio (PSNR) is used to measure imperceptibility of the digital image while normalize cross correlation (NCC) is applied to measure the robustness of digital image. The performance evaluations of the proposed method were implemented in MATLAB. The results showed that the described method imperceptible of HL level sub-bands than other levels of sub-bands. While the robustness is achieved by all levels sub-bands.

Optimasi Keamanan Watermarking pada Daubechies Transform Berbasis Arnold Cat Map

Digital image security using Transform Domain algorithms such as Discrete Wavelet Transform (DWT) has been widely used. To improve the security of the DWT algorithm needs to randomize the pixel coefficient, namely Arnold Cat Map (ACM). Computing ACM as one of the chaos functions is known to be fast and fits with Transform Domain. DWT has been implemented in the Daubechies filter which is the development of the Haar filer. In this paper, we proposed the message insertion model using a combination of DWT and ACM on a 512x512 piskel grayscale image and a 64x64 pixel message on the LL subband. The experiments were performed on 2 different images to determine the ability produced by the combined algroithm. The ability test for message insertion process is done through Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and comparation between original image histogram and image insertion histogram. While in the process of message extraction, algorithmic capability test is done by calculating Normalized Cross Correlation (NCC) and its correlation. The highest MSE result is 2.9502 and the highest PSNR is 43.4323 dB, while the NCC value is 237.3584 with correlation 0.7181.

Multi-focus image fusion algorithm based on focus detection in spatial and NSCT domain.

Multi-focus image fusion is an effective approach to obtain the all-in-focus image. Focus detection is the key issue of multi-focus image fusion. Aiming at the shortcoming of spatial domain and transform domain algorithms for multi-focus image fusion, a novel multi-focus image fusion algorithm is proposed by combing focus detection in spatial domain and non-subsampled contourlet transform (NSCT) domain. At first, the focused pixels are detected by the sum-modified-Laplacian algorithm in spatial domain. At the same time, the focus detection method is proposed in NSCT domain, namely by MPCNN and voting fusion methods for high-frequency subbands of NSCT. Then, the morphological operation is utilized to correct the focus detection results in spatial domain and NSCT domain. At last, synthesis of detection results is implemented and the fused image can be obtained. Experimental results verified that the proposed algorithm outperformed some state-of-the-art fusion algorithms in terms of both subjective observation and objective evaluations.

A double random phase encoding approach for cancelable iris recognition

In a cancelable iris recognition technique, all enrollment patterns are masked using a transformation function, and the invertibility process for obtaining the original data should not be possible. A novel cancelable iris authentication approach in the encrypted domain is presented in this paper. The double random phase encoding (DRPE) algorithm in the Fractional Fourier Transform (FrFT) Domain is utilized to generate the optical masked IrisCodes. For the transmitter side, two encryption keys (RPM1 and RPM2) are utilized, while the second phase mask is proposed to be the right iris feature vector of the same user. As a result, mixing the feature vectors of the left and right iris patterns of the same subject to an encrypted IrisCode results in enhancing the privacy and preserving the system performance. This proposed system success is attributed to the fact that the iris authentication issue is transformed to a key authentication process. Experimental results conducted on CASIA-IrisV3-Interval dataset achieve a significant gain for both privacy and performance proving the superiority of the proposed approach.

Multiple-Image Hiding by Using Single-Shot Ptychography in Transform Domain

A practical method using single-shot ptychographic imaging (SPI) in the transform domain is proposed for multiple-image hiding. The excellent compressibility of SPI can bring high multiplexing capacity and imperceptibility to the proposed multiple-image hiding system. The security is mainly supported by the imperceptibility and the large quantity of scrambling modes, and security will be improved greatly with the increase of hidden images. Furthermore, the successful combination with the discrete cosine transform-domain algorithm can not only further enhance the imperceptibility and security but indicates that SPI-based multiple-image hiding is compatible with transform domain algorithms as well. Optical experiments demonstrate the high feasibility, multiplexing capacity, imperceptibility, and security of the proposed technique. The proposed method may open up a novel research perspective for multiple-image hiding combined with various efficient transform domain algorithms.

A Strong Interference Suppressor for Satellite Signals in GNSS Receivers

In this paper, we discuss a method to protect satellite signals from strong time-varying interferers. Time-domain, transform-domain, and space-domain algorithms have been widely used for interference suppression. However, when used under high dynamic conditions, these methods cause serious suppression of satellite signals in the GPS receivers along with inhibiting interferers. To address this problem, we optimize the satellite and interference steering vectors using a multi-star forming approach to distinguish satellite signals and strong interferers. In order to detect time-varying interferers, we further introduce a novel hidden Markov model (HMM), and power inversion (PI) and Multi-star interference suppressed (Multi-PI) model anti-interference synthesis scheme.A bank of HMM filters are operated to track the on–off interferers in the frequency domain, and decide if an anti-interference algorithm needs to be used. After HMM, the Multi-PI algorithm is implemented to inhibit broadband interferers. The experimental results show that our novel scheme adapts quickly when tracking time-varying interferers and protects GPS signals from losses.

A low-complexity image compression approach with single spatial prediction mode and transform

The well-known low-complexity JPEG and the newer JPEG-XR systems are based on block-based transform and simple transform-domain coefficient prediction algorithms. Higher complexity image compression algorithms, obtainable from intra-frame coding tools of video coders H.264 or HEVC, are based on multiple block-based spatial-domain prediction modes and transforms. This paper explores an alternative low-complexity image compression approach based on a single spatial-domain prediction mode and transform, which are designed based on a global image model. In our experiments, the proposed single-mode approach uses an average 20.5 % lower bit-rate than a standard low-complexity single-mode image coder that uses only conventional DC spatial prediction and 2-D DCT. It also does not suffer from blocking effects at low bit-rates.

All-layer search algorithm using mean inequality and improved checkerboard partial distortion search for fast motion estimation

Block-matching motion estimation algorithm is used in many video compression coding systems because it could greatly reduce the temporal redundancy between the consequent video sequences. In this paper, an all-layer search algorithm using mean inequality and improved checkerboard partial distortion search scheme for fast block-matching motion estimation is proposed. A layer in the proposed method refers to a processed image which is derived from the reference frame or the adjacent lower layer. Firstly, the proposed algorithm constructs all layers from the reference frame or the adjacent lower layer by summing up all pixels over a sub-block. Then, a new mean inequality elimination method is introduced to reject a lot of unnecessary candidate search points on the top layers before calculating the real block matching distortion. Finally, the proposed algorithm utilizes an improved checkerboard partial distortion search scheme in the process of the real block distortion calculation on the following layers to further reduce the amount of computation. Experimental results show that the proposed algorithm can effectively reduce the computational complexity of motion estimation meanwhile guarantee the matching quality compared to other motion estimation algorithms. Compared to the full search algorithm, the proposed algorithm can reduce 97.30 % computational complexity with a negligible degradation of the peak signal to noise ratio (PSNR). Compared to the diamond search algorithm, directional gradient descent search algorithm, partial distortion search algorithm, transform-domain successive elimination algorithm and two-layer motion estimation algorithm, the proposed algorithm can also save 63.56 %, 52.73 %, 92.87 %, 85.77 % and 33.96 % computational complexity, respectively.

An Iterative Semi Blind Transform Domain Watermarking

Digital Watermarking is an efficient way of securing various multimedia contents. An Iterative semi-blind watermarking technique is proposed in this research for gray scale images, based on Transform Domain and Independent Component Analysis (ICA) Algorithms. Transform Domain includes Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD). In embedding process, the watermark is embedded into singular values of the host image's DCT coefficients. The host image and the secret image are considered as two separate signals and combined using the Fast-ICA Algorithm, a variant of Independent Component Analysis (ICA) mixing model, to generate the watermarked image and is also used to extract the watermark efficiently. The statistical property of the Fast-ICA Algorithm extracts the watermark differently at different time and hence the watermark is extracted repeatedly until the Normalized Cross Correlation (NCC) is above a certain threshold value to extract a clear watermark. The metrics Peak Signal to Noise Ratio (PSNR) and NCC are computed to measure the quality of watermarked image and extracted watermark respectively. This method increases the capacity, robustness and security than the Discrete Wavelet Transform (DWT) combined with SVD and Fast-ICA where the watermark is embedded and extracted from the low frequency band.

An Affinity-Based Algorithm in Nonsubsampled Contourlet Transform Domain: Application to Synthetic Aperture Radar Image Denoising

An algorithm in which affinity is merged into nonsubsampled contourlet transform (NSCT) to denoise synthetic aperture radar (SAR) image is proposed. The important information (boundaries or details) or non-important information (homogeneous area) in a SAR image is estimated based on affinity matrix, by which the affinity-based denoising assigns a high affinity element to the coefficients of NSCT that belong to same region. The foreground and background in NSCT domain are automatically initialized which avoids the need for user initialization. Foreground probability obtained by optimizing objective function can be used to achieve the posterior ratio. Combining the posterior ratio and prior ratio, we can obtain the shrunk coefficients. The proposed algorithm was applied to real SAR images denoising and compared through the SAR image vision effect, the equivalent number of looks (ENL) and the edge sustain index (ESI). Experimental results show that the proposed algorithm outperforms the compared algorithms and achieves the better denoising result and edge preservation.

Digital Image Watermarking Algorithms Based on Dual Transform Domain and Self-Recovery

Abstract In view of dual watermarking algorithm for dual two value image watermarking, the watermark information there is a gray image watermarking in the expression is obviously insufficient. The proposed embedded in the carrier image on the dual watermark includes a two watermark image and a gray image watermarking algorithm, the persuasive power while maintaining the original two values of the watermark robustness at the same time, improve the watermark information. In order to balance the robustness and invisibility of watermarking algorithm, this paper analyzes the embedding position and strategy of transform domain algorithms, the DC coefficient in the carrier image is divided into blocks of DCT spectrum and spectrum on the combination of DWT coefficient method and the advantage of embedded dual watermarking, and use the NEC characteristic of the algorithm is improved adaptive based on the embedded mode. The gray image watermark bit plane decomposition compression high four bit plane information as watermarking, in reducing the original watermark loading and enhance the overall strength of self recovery system. This paper from the working principle, classification of digital watermarking, attack types, performance index, evaluation method and uses six aspects were introduced to the digital watermarking technology. Simulation study of a digital image watermarking algorithm based on DCT transform and Arnold transform, the algorithm’s imperceptibility, robustness and security are analyzed, the algorithm for embedding process.