Sharif Digital Repository

Adaptive filtering has been used for speech denoising in the time domain. During the last decade, wavelet transform has been developed for speech enhancement. In this paper we are proposing to use adaptive filtering in the Wavelet transform domain. We propose a hybrid method of using adaptive filters on the lower scales of a wavelet transformed speech together with the conventional methods (Thresholding, Spectral Subtraction, and Wiener filtering) on the higher scale coefficients. Experimental results demonstrate that the suggested approach is computationally efficient and has a good performance. © 2005 IEEE  

Integrity verification or forgery detection of an image is a difficult procedure, since the forgeries use various transformations to create an altered image. Pixel mapping transforms, such as contrast enhancement, histogram equalisation, gamma correction and so on, are the most popular methods to improve the objective property of an altered image. In addition, fabricators add Gaussian noise to the altered image in order to remove the statistical traces produced because of pixel mapping transforms. A new method is introduced to detect and classify four various categories including original, contrast modified, histogram-equalised and noisy images. In the proposed method, the absolute value of... 

Capacity approximation of multi-hop unicast and multi-hop multicast channels is one of unsolved problems in information theory. Recently some researches investigate Degrees of Freedom (DoF) characterization and Interference Alignment schemes for these channels. However most of them assumed perfect instantaneous Channel State Information (CSI) at the relays and the transmitters. Due to practical limitations, like the delay and the rate limitation in the feedback links and the fading channels, it is difficult to provide perfect instantaneous CSI at the transmitters and even the relays. Achievable DoF by the IA schemes collapses greatly with imperfect CSI. It has been shown that the delayed CSI... 

Interference Alignment (IA) is a rather new technique to achieve higher Degrees-of-Freedom (DoF) compared to traditional orthogonal naive methods, like, Time Division Multiple Access (TDMA). In many IA schemes, Instantaneous Channel State Information at Transmitter (CSIT) is mandatory. However, this requirement becomes an obstacle to implement those methods in practice. In some practical scenarios, it is not possible to provide instantaneous or even delayed CSIT. Recently, Blind Interference Alignment (BIA) has been introduced as a solution to align interference without CSIT. In spit of major advances in single-hop Interference Channels (ICs), few researches focused on multi-hop ICs. In this... 

In this study, a blind steganalysis approach which accurately discloses low rate data hiding schemes is proposed. The absolute values of neighbouring joint density (absNJ) are used for feature extraction. In this way, the intra- and inter-block situations are employed providing a variety of different features. Aside from the absolute values of discrete cosine transform (DCT) coefficients, the differential DCT coefficients are also exploited to extract the features. Moreover, the absNJ features will be extended and used over differential DCT coefficients. It is shown that applying the Pth power of the DCT coefficients instead of their first power gains more discriminative features. Then,... 

This paper proposes a novel combinational Adaptive Noise Canceller (ANC), which is suitable for non stationary noise environments. Pre-filter bank structure improves the convergence rate leading to less error in real-time applications. During our investigations, we have found out adaptive algorithms have better performance for low frequency subbands. Thus, by using Singular Value Decomposition (SVD) in each subband, a simplified version of variable step-size algorithms has been employed in low frequency subbands; while for high frequency subbands, some conventional techniques have been used. Simulation results show that combination of adaptive and conventional methods have better performance... 

In this paper, a novel blind watermarking technique based on quantization is proposed. Quantization is performed in a special domain which converts one dimensional signal to a 2-D one named Point to Point Graph (PPG). Basis of the method is on the separation of this domain into two portions; while, only one portion is quantized. Furthermore, in the dewatermarking procedure, by using the unquantized portion and zero norm, the embedded data can be extracted. The performance of the proposed method is analytically investigated and verified by simulation with artificial Gaussian signals. Experimental results over several audio signals shows the great robustness of the technique in comparison with... 

In this paper a novel hybrid algorithm for compensating the distortion of any interpolation has been proposed. In this Hybrid method, a modular approach was incorporated in an iterative fashion. The proposed technique features an impressive improvement at reduced computational complexity. The authors also extend the scheme to 2-D signals and actual (real) images and find that the solution exhibits great potential. Both the simulation results and mathematical analysis confirm the superiority of the Hybrid model over competing methods and demonstrate its robustness against additive noise  

In this paper we extended a previously investigated modular method that is designed to compensate for interpolation distortions of one-dimensional signals, to two dimensions (2-D). Next the proposed 2-D modular technique was applied in an iterative fashion and was shown through both simulations and theoretical analyses to enhance the convergence of the iterative technique. In fact, with only a few modules we were able to achieve drastic improvements in signal reconstruction, and with a much less computational complexity. Moreover, both the simulations and the theoretical analysis confirmed the robustness of the proposed scheme against additive noise  

A blind semi-invertible quantization based data hiding scheme, which reconstructs the original signal with high precision has been proposed. In order to produce correlated quantization yielding reversibility of the quantization based approach, a new transform domain has been introduced. In decoder, by compensating the quantization error and using the iterative technique, the original signal is recovered; then the watermarked signal is compared with the reconstructed original signal and hidden data is retrieved. Simulation results show that the proposed method in comparison with other reversible methods imposes less distortion and thus a higher Signal to Noise Ratio (SNR) is achieved. © 2009... 

This paper considers the problem of covert communication through dedicated voice channels by embedding secure data in the cover speech signal utilizing spread spectrum additive data hiding. The cover speech signal is modeled by a Generalized Gaussian (GGD) random variable and the Maximum A Posteriori (MAP) detector for extraction of the covert message is designed and its reliable performance is verified both analytically and by simulations. The idea of adaptive estimation of detector parameters is proposed to improve detector performance and overcome voice non-stationarity. The detector's bit error rate (BER) is investigated for both blind and semi-blind cases in which the GGD shape... 

Among the many attacks against watermarked data, the gain attack is less supported with countermeasures. The effectiveness of this attack becomes more evident in quantization-based embedding algorithms such as Dither Modulation (DM). In this paper, the general solution for both block and sample type DM schemes that are robust against gain attacks is considered. Among the solutions, we concentrate on a subclass of the algorithms which are insensitive to additive noise attacks; i.e., we introduce watermarking schemes which are both robust against gain and additive noise attacks. The simulation results confirm the desired performance of the final algorithm against these attacks while outperform... 

The rapid development and growth of cellular mobile networks in recent years has made voice channels widely available almost everywhere. On the other hand, voice dedicated channels possess properties that make them ideal options for high priority real-time secure communications. Beside these realities, information embedding has gained remarkable attention in recent years due to its potential application in multimedia security. In this regard, this study aims to propose an efficient scheme for data hiding to show the feasibility of exploiting these channels for covert communications. To this end, the authors propose new suboptimal but practical schemes based on additive and multiplicative... 

In this paper, a novel quantization based watermarking method is proposed. For blind detection, a set of nonlinear convex functions based on geometric mean are investigated. In order to achieve minimum distortion, the optimum function set is found. The algorithm is implemented on the approximation coefficients of wavelet transform for natural images. In order to make the algorithm more robust and imperceptible, a new transform domain called Point to Point Graph (PPG), which converts a 1-D signal to a 2-D one, has been used. The error probability of the proposed scheme is analytically investigated. Simulation results show that this algorithm has great robustness against common attacks such as... 

The swift growth of cellular mobile networks in recent years has made voice channels almost accessible everywhere. Besides, data hiding has recently attracted significant attention due to its ability to imperceptibly embed side information that can be used for signal enhancement, security improvement, and two-way authentication purposes. In this regard, we aim at proposing efficient schemes for hiding data in the widespread voice channel of cellular networks. To this aim, our first contribution is to model the channel accurately by considering a linear filter plus a nonlinear scaling function. This model is validated through experiments with true speech signals. Then we leverage on this... 

In this paper, the application of a well known mathematical theorem, Banach's fixed point theorem [1], is investigated in iterative signal processing in communications. In most practical communication systems some sort of a contraction mapping is used to enhance the operation of the system. Thus, using a suitable iterative approach, one can set the system in its fixed point and hence, the distortion produced in the transmitter, channel and the receiver can be compensated. In other words, a loosely designed transceiver can be enhanced by an iterative method. In order to verify the truth of the proposed iterative method, the distortion of A/D and D/A converters is compensated at the receiver.... 

This paper presents a novel approach to audio signals watermarking in the wavelet or the Walsh transform domain. The idea is to embed watermark data in the coefficients of some scales of the transform domain. The overall bit rate of this method is about 90 bps. Due to low computational complexity of the suggested approach, particularly in the Walsh domain, this algorithm can be implemented in real time. Experimental results show robustness of the proposed method in low SNRs and also against some typical attacks, such as MP3 compression, echo, filtering, etc. Subjective evaluation confirms transparency of the watermarked audio signals. © 2006 IEEE  

In this paper, an improved multiplicative image watermarking system is presented. Since human visual system is less sensitive to the image edges, watermarking is applied in the contourlet domain, which represents image edges sparsely. In the presented scheme, watermark data is embedded in directional subband with the highest energy. By modeling the contourlet coefficients with General Gaussian Distribution (GGD), the distribution of watermarked noisy coefficients is analytically calculated. The tradeoff between the transparency and robustness of the watermark data is solved in a novel fashion. At the receiver, based on the Maximum Likelihood (ML) decision rule, an optimal detector by the aid... 

In this paper, a semi-blind multiplicative watermarking approach for audio and speech signals has been presented. At the receiver end, the optimal maximum likelihood (ML) detector aided by the archived information for Gaussian and Laplacian signals in noisy environment is designed and implemented. The performance of the proposed scheme is analytically calculated and verified by simulation. Then, we adapt the proposed scheme to speech and audio signals. To improve robustness, the algorithm is applied to low frequency components of the host signal. Besides, the power of the watermark is controlled elegantly to have inaudibility using perceptual evaluation of audio quality (PEAQ) and perceptual... 

In this paper, a semi-blind multiplicative watermarking approach for audio and speech signals has been presented. At the receiver end, the optimal Maximum Likelihood (ML) detector aided by the channel side information for Gaussian and Laplacian signals in noisy environment is designed and implemented. The performance of the proposed scheme is analytically calculated and verified by simulation. Then, we adapt the proposed scheme to speech and audio signals. To improve robustness, the algorithm is applied to low frequency components of the host signal. Besides, the power of the watermark is controlled elegantly to have inaudibility using Perceptual Evaluation of Audio Quality (PEAQ) and...