Sharif Digital Repository

In this paper we introduce two innovative image and video watermarking algorithms. The paper's main emphasis is on the use of chaotic maps to boost the algorithms' security and resistance against attacks. By encrypting the watermark information in a one dimensional chaotic map, we make the extraction of watermark for potential attackers very hard. In another approach, we select embedding positions by a two dimensional chaotic map which enables us to satisfactorily distribute watermark information throughout the host signal. This prevents concentration of watermark data in a corner of the host signal which effectively saves it from being a target for attacks that include cropping of the... 

Conventional implementation of multi-dimensional wavelet transform (e.g. 3-D wavelet) requires whether a high amount of "in access" memory or a continual access to slow memory of a processor which makes it infeasible for most applications. In this paper, we proposed a novel algorithm for computation of an n-D discrete wavelet transform (DWT) based on lifting scheme. In addition to benefits of lifting scheme (which causes a major reduction in computational complexity and performs the total computations in time domain), our real-time approach computes the coefficients for all kinds of 1st and 2 nd generation wavelets with short delay and optimized utilization of the slow and fast memories of a... 

This paper puts forth a wavelet-based methodology for generating endurance time (ET) excitations. Conventional simulating practice expresses signals by acceleration values which are then computed via unconstrained nonlinear optimization. Dynamic characteristics of signals, including frequency content, are not represented directly in this type of variable definition. In this study, a new algorithm is developed to generate ET excitations in discrete wavelet transform (DWT) space. In this algorithm, signals are represented by transform coefficients. In addition, objective functions are modified in order to obtain transform coefficients and return the objective function values. The proposed... 

In this paper, we present the most general form for error control coding using finite field multi-rate filters. This method shows how different types of codes can easily be generated by multi-rate filters and filter banks. In all previous works, codes and syndromes were generated using prefilters. Here we present simple multi-rate structures for encoding and generating syndrome. We show that all kinds of arbitrary rate K/L, circulant linear codes can be generated by these structures. Then we claim that a similar simple structure for syndrome generation in all presented cases exist  

We have presented a new method for ECG baseline correction using the adaptive bionic wavelet transform (BWT). In fact by the means of BWT, the resolution in the time-frequency domain can be adaptively adjusted not only by the signal frequency but also by the signal instantaneous amplitude and its first-order differential. Besides by optimizing the BWT parameters parallel to modifying our previous thresholding rule, one can handle ECG baseline correction. First an estimation of the baseline wandering frequency is obtained and then the adaptation can be used only in three successive scales in which the mid-scale has the closest center frequency to the estimated frequency. Thus the... 

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  

A new robust image adaptive digital watermarking algorithm in wavelet transform domain is proposed in this paper. The proposed method exploits Human Visual System (HVS) characteristics and entropy masking concept to determine image adaptive thresholds for selection of perceptually significant coefficients. The mark is embedded in the coefficients of all subbands including the LL subband. Experimental results show that the proposed method significantly improves watermarking performance over conventional methods, in the terms of invisibility and robustness  

An improved compression algorithm for ECG signals is presented using temporal alignment of beats and 2-D wavelet packet transform (WPT). This 2-D transform based approach utilizes the fact that the electrocardiogram (ECG) signals generally show two types of correlation, namely correlation between subsequent samples within each ECG cycle (intrabeat) and correlation between subsequent cycles (interbeat). One simple compression algorithm in the 2-D WPT domain, which is applied to some records in the MIT-BIH arrhythmia database shows lower percent root mean square difference (PRD) than 1-D wavelet based compression methods for the same compression ratio (CR). © 2001 IEEE  

Video activity analysis is used in various video applications such as human action recognition, video retrieval, video archiving. In this paper, we propose to apply 3D wavelet transform statistics to natural video signals and employ the resulting statistical attributes for video modeling and analysis. From the 3D wavelet transform, we investigate the marginal and joint statistics as well as the Mutual Information (MI) estimates. We show that marginal histograms are approximated quite well by Generalized Gaussian Density (GGD) functions; and the MI between coefficients decreases when the activity level increases in videos. Joint statistics attributes are applied to scene activity grouping,... 

In this paper, we present a novel speech steganography method using discrete wavelet transform and sparse decomposition to address the undetectability concern in speech steganography. The proposed speech steganography method exploits the sparse representation to embed secret messages into higher semantic levels of the cover signal, resulting in increased undetectability. The proposed method also yields improvements on both stego signal quality and embedding capacity, which are the two major requirements of a steganography algorithm. Our experimental results illustrate that the stego signals generated by the proposed method are perceptually indistinguishable from the original cover signals,... 

A novel photoacoustic microscopy (PAM) structure, based on Haar wavelet patterns, is proposed in this paper. Its main goal is to mitigate the PAM imaging resolution and thus the time of its sampling process without compromising the image quality. Owing to the intrinsic nature of wavelet transform, this structure collects spatial and spectral components simultaneously, and this feature speeds up the sampling process by 33%. The selection of these patterns helps in better control of required conditions, such as multi-resolution imaging, to guarantee adequate image quality in comparison to previous microscopic structures. Simulation results prove the superior quality of the proposed approach... 

A novel photoacoustic microscopy (PAM) structure, based on Haar wavelet patterns, is proposed in this paper. Its main goal is to mitigate the PAM imaging resolution and thus the time of its sampling process without compromising the image quality. Owing to the intrinsic nature of wavelet transform, this structure collects spatial and spectral components simultaneously, and this feature speeds up the sampling process by 33%. The selection of these patterns helps in better control of required conditions, such as multi-resolution imaging, to guarantee adequate image quality in comparison to previous microscopic structures. Simulation results prove the superior quality of the proposed approach... 

This study aims to show the efficiency of a proposed spectral matching technique for the reduction of required ground motions in the dynamic time history analysis. In this non-stationary spectral matching approach, unconstrained optimization is employed to adjust the signal to match a target spectrum. Adjustment factors of discrete wavelet transform (DWT) coefficients associated with the signals are then considered as decision variables and the Levenberg-Marquardt algorithm is employed to find the optimum values of DWT coefficients. This matching algorithm turns out to be quite effective in the spectral matching objective, where matching at multiple damping ratios can be readily achieved.... 

A video activity analysis is presented based on 3D wavelet transform. Marginal and joint statistics as well as mutual information estimates are extracted. Marginal histograms are approximated by Generalized Gaussian Density (GGD) functions. The mutual information between coefficients -as a quantitative estimate of joint statistics- decreases when the activity in the video increases. The relationship between kurtosis graphs, extracted from joint distributions and video activity, is deduced. Results show that the type of activity in the video can be figured out from Kurtosis curves. The GGD and the Kullback-Leibler distance (KLD) are used to retrieve and locate 96% of videos properly  

In this paper we make use of M-band discrete wavelet transform (MDWT) and Wiener filter for speckle noise suppression of ultrasound images. Assuming multiplicative model for speckle noise, by applying logarithmic transform to noisy observation we convert multiplicative noise to additive one. Then, speckle noise can be reduced by taking the M-band wavelet transform of log-transformed observation and employing an adaptive thresholding technique. In order to improve the performance of this denosing approach, we propose a preprocessing stage which exploits Wiener filtering. Through this stage logtransformed observation is separated into two images and then each of these two images is denoised... 

We present a new modified wavelet transform, called the multiadaptive bionic wavelet transform (MABWT), that can be applied to ECG signals in order to remove noise from them under a wide range of variations for noise. By using the definition of bionic wavelet transform and adaptively determining both the center frequency of each scale together with the T-function, the problem of desired signal decomposition is solved. Applying a new proposed thresholding rule works successfully in denoising the ECG. Moreover by using the multiadaptation scheme, lowpass noisy interference effects on the baseline of ECG will be removed as a direct task. The method was extensively clinically tested with real... 

In this paper a new ECG denoising scheme is proposed using a novel adaptive wavelet transform, named bionic wavelet transform (BWT), which had been first developed based on a model of the active auditory system. There has been some outstanding features with the BWT such as nonlinearity, high sensitivity and frequency selectivity, concentrated energy distribution and its ability to reconstruct signal via inverse transform but the most distinguishing characteristic of BWT is that its resolution in the time-frequency domain can be adaptively adjusted not only by the signal frequency but also by the signal instantaneous amplitude and its first-order differential. Besides by optimizing the BWT... 

The objective of this research is to diagnose an inaccessible rolling bearing by indirect vibration measurement. In this study, a shaft supported with several bearings is considered. It is assumed that the vibration for at least one bearing is not recordable. The purpose is to diagnose inaccessible bearing by the recorded data from the sensors located on the other bearings. To achieve this goal, the continuous wavelet transform is used to detect weak signatures in the available vibration signals. A new criterion for adjusting the scale parameter of continuous wavelet transform is proposed based on the amplitude of the bearing characteristic frequencies. In this criterion, the optimal scale... 

The Wavelet based speech enhancement is considered. In this method, the noisy signal transfers to wavelet domain. Then with applying a thresholding algorithm, the wavelet coefficients will be improved. At last using the inverse wavelet transform the enhanced signal will be obtained. In this paper, we have presented a new method for thresholding algorithm. We compared our algorithm with some of the most popular methods by several experimental tests. Both subjective and objective tests show better performance and achievements