Optimum Watermark Detection and Embedding in Digital Images

This work concentrates on the problem of watermarking of still images using the luminance component, through the use of spread spectrum techniques, both in space (direct sequence spread spectrum or DSSS) and frequency (frequency hopping or FH), following the guidelines of Delaigle et al. (1998). The system described is able to embed watermarks and recover them with zero probability of error. The problem is faced from a statistical detection point of view through the analysis of the density function of the image to be marked. A Cauchy model is found to be very accurate and some tests are performed in order to assess improved detection quality. The resulting system turns out to be easy to encrypt and very robust to filtering and JPEG compression.Peer ReviewedPostprint (published version

IEEE TRANSACTIONS ON COMMUNICATIONS, ACCEPTED FOR PUBLICATION 1 Decision Boundary Evaluation of Optimum and Suboptimum Detectors in Class-A Interference

Abstract-The Middleton Class-A (MCA) model is one of the most accepted models for narrow-band impulsive interference superimposed to additive white Gaussian noise (AWGN). The MCA density consists of a weighted linear combination of infinite Gaussian densities, which leads to a non-tractable form of the optimum detector. To reduce the receiver complexity, one can start with a two-term approximation of the MCA model, which has only two noise states (Gaussian and impulsive state). Our objective is to introduce a simple method to estimate the noise state at the receiver and accordingly, reduce the complexity of the optimum detector. Furthermore, we show for the first time how the decision boundaries of binary signals in MCA noise should look like. In this context, we provide a new analysis of the behavior of many suboptimum detectors such as a linear detector, a locally optimum detector (LOD), and a clipping detector. Based on this analysis, we insert a new clipping threshold for the clipping detector, which significantly improves the bit-error rate performance

Data hidding in color images using perceptual models

One of the problems arising from the use of digital media is the ease of identical copies of digital images or audio files, allowing manipulation and unauthorized use. Copyright is an effective tool for preserving intellectual property of those documents but authors and publishers need effective techniques that prevent from copyright modification, due to the straightforward access to multimedia applications and the wider use of digital publications through the www. These techniques are generally called watermarking and allow the introduction of side information (i.e. author identification, copyrights, dates, etc.). This work concentrates on the problem embedding and optimum blind detection of data in color images through the use of spread spectrum techniques, both in space (Direct Sequence Spread Spectrum or DSSS) and frequency (Frequency Hopping). It is applied to RGB and opponent color component representations. Perceptive information is considered in both color systems. Some tests are performed in order to ensure imperceptibility and to assess detection quality of the optimum color detectors.Peer ReviewedPostprint (published version

Stochastic resonance in chua's circuit driven by alpha-stable noise

Thesis (Master)--Izmir Institute of Technology, Electronics and Communication Engineering, Izmir, 2012Includes bibliographical references (leaves: 75-80)Text in English; Abstract: Turkish and Englishx, 80 leavesThe main aim of this thesis is to investigate the stochastic resonance (SR) in Chua's circuit driven by alpha-stable noise which has better approximation to a real-world signal than Gaussian distribution. SR is a phenomenon in which the response of a nonlinear system to a sub-threshold (weak) input signal is enhanced with the addition of an optimal amount of noise. There have been an increasing amount of applications based on SR in various fields. Almost all studies related to SR in chaotic systems assume that the noise is Gaussian, which leads researchers to investigate the cases in which the noise is non-Gaussian hence has infinite variance. In this thesis, the spectral power amplification which is used to quantify the SR has been evaluated through fractional lower order Wigner Ville distribution of the response of a system and analyzed for various parameters of alpha-stable noise. The results provide a visible SR effect in Chua’s circuit driven by symmetric and skewed-symmetric alpha-stable noise distributions. Furthermore, a series of simulations reveal that the mean residence time that is the average time spent by the trajectory in an attractor can vary depending on different alpha-stable noise parameters

Improved time-frequency de-noising of acoustic signals for underwater detection system

The capability to communicate and perform target localization efficiently in underwater environment is important in many applications. Sound waves are more suitable for underwater communication and target localization because attenuation in water is high for electromagnetic waves. Sound waves are subjected to underwater acoustic noise (UWAN), which is either man-made or natural. Optimum signal detection in UWAN can be achieved with the knowledge of noise statistics. The assumption of Additive White Gaussian noise (AWGN) allows the use of linear correlation (LC) detector. However, the non-Gaussian nature of UWAN results in the poor performance of such detector. This research presents an empirical model of the characteristics of UWAN in shallow waters. Data was measured in Tanjung Balau, Johor, Malaysia on 5 November 2013 and the analysis results showed that the UWAN has a non-Gaussian distribution with characteristics similar to 1/f noise. A complete detection system based on the noise models consisting of a broadband hydrophone, time-frequency distribution, de-noising method, and detection is proposed. In this research, S-transform and wavelet transform were used to generate the time-frequency representation before soft thresholding with modified universal threshold estimation was applied. A Gaussian noise injection detector (GNID) was used to overcome the problem of non-Gaussianity of the UWAN, and its performance was compared with other nonlinear detectors, such as locally optimal (LO) detector, sign correlation (SC) detector, and more conventionally matched filter (MF) detector. This system was evaluated on two types of signals, namely fixed-frequency and linear frequency modulated signals. For de-noising purposes, the S-transform outperformed the wavelet transform in terms of signal-to-noise ratio and root-mean-square error at 4 dB and 3 dB, respectively. The performance of the detectors was evaluated based on the energy-to-noise ratio (ENR) to achieve detection probability of 90% and a false alarm probability of 0.01. Thus, the ENR of the GNID using S-transform denoising, LO detector, SC detector, and MF detector were 8.89 dB, 10.66 dB, 12.7dB, and 12.5 dB, respectively, for the time-varying signal. Among the four detectors, the proposed GNID achieved the best performance, whereas the LC detector showed the weakest performance in the presence of UWAN

Analysis of low-density parity-check codes on impulsive noise channels

PhD ThesisCommunication channels can severely degrade a signal, not only due to fading effects but also interference in the form of impulsive noise. In conventional communication systems, the additive noise at the receiver is usually assumed to be Gaussian distributed. However, this assumption is not always valid and examples of non-Gaussian distributed noise include power line channels, underwater acoustic channels and manmade interference. When designing a communication system it is useful to know the theoretical performance in terms of bit-error probability (BEP) on these types of channels. However, the effect of impulses on the BEP performance has not been well studied, particularly when error correcting codes are employed. Today, advanced error-correcting codes with very long block lengths and iterative decoding algorithms, such as Low-Density Parity-Check (LDPC) codes and turbo codes, are popular due to their capacity-approaching performance. However, very long codes are not always desirable, particularly in communications systems where latency is a serious issue, such as in voice and video communication between multiple users. This thesis focuses on the analysis of short LDPC codes. Finite length analyses of LDPC codes have already been presented for the additive white Gaussian noise channel in the literature, but the analysis of short LDPC codes for channels that exhibit impulsive noise has not been investigated. The novel contributions in this thesis are presented in three sections. First, uncoded and LDPC-coded BEP performance on channels exhibiting impulsive noise modelled by symmetric -stable (S S) distributions are examined. Different sub-optimal receivers are compared and a new low-complexity receiver is proposed that achieves near-optimal performance. Density evolution is then used to derive the threshold signal-tonoise ratio (SNR) of LDPC codes that employ these receivers. In order to accurately predict the waterfall performance of short LDPC codes, a nite length analysis is proposed with the aid of the threshold SNRs of LDPC codes and the derived uncoded BEPs for impulsive noise channels. Second, to investigate the e ect of impulsive noise on wireless channels, the analytic BEP on generalized fading channels with S S noise is derived. However, it requires the evaluation of a double integral to obtain the analytic BEP, so to reduce the computational cost, the Cauchy- Gaussian mixture model and the asymptotic property of S S process are used to derive upper bounds of the exact BEP. Two closed-form expressions are derived to approximate the exact BEP on a Rayleigh fading channel with S S noise. Then density evolution of different receivers is derived for these channels to nd the asymptotic performance of LDPC codes. Finally, the waterfall performance of LDPC codes is again estimated for generalized fading channels with S S noise by utilizing the derived uncoded BEP and threshold SNRs. Finally, the addition of spatial diversity at the receiver is investigated. Spatial diversity is an effective method to mitigate the effects of fading and when used in conjunction with LDPC codes and can achieve excellent error-correcting performance. Hence, the performance of conventional linear diversity combining techniques are derived. Then the SNRs of these linear combiners are compared and the relationship of the noise power between different linear combiners is obtained. Nonlinear detectors have been shown to achieve better performance than linear combiners hence, optimal and sub-optimal detectors are also presented and compared. A non-linear detector based on the bi-parameter Cauchy-Gaussian mixture model is used and shows near-optimal performance with a significant reduction in complexity when compared with the optimal detector. Furthermore, we show how to apply density evolution of LDPC codes for different combining techniques on these channels and an estimation of the waterfall performance of LDPC codes is derived that reduces the gap between simulated and asymptotic performance. In conclusion, the work presented in this thesis provides a framework to evaluate the performance of communication systems in the presence of additive impulsive noise, with and without spatial diversity at the receiver. For the first time, bounds on the BEP performance of LDPC codes on channels with impulsive noise have been derived for optimal and sub-optimal receivers, allowing other researchers to predict the performance of LDPC codes in these type of environments without needing to run lengthy computer simulations