Search

Blind noise-level estimation (NLE) is a fundamental issue in digital image processing. This paper provides a noise-level estimator for additive white Gaussian noise and multiplicative Gaussian noise using principal texture patches (PTPs). The proposed algorithm first identifies the principal texture of the noisy image by using the principal component analysis, and then, it chooses PTPs to calculate the noise level. The major contributions of this paper toward addressing the challenges in the NLE literature include: 1) analyzing the nonlinear relationship between the smallest eigenvalue, true noise level, number of chosen patches, and block size; 2) extracting PTPs; and 3) computing noise level using PTPs. The abundant experimental results show that the proposed method works well for various natural images over a large range of noise levels and it performs well for multiplicative noise. Compared with some state-of-the-art approaches, our method has the best performance and a faster running speed. [ABSTRACT FROM AUTHOR]

In this letter, a novel method has been proposed, which includes formulation of similarity function and a fuzzy-based method for filtering mixed noise. The similarity function is adaptive to local noise level and edge information, and it is used to detect similarity among pixels in a peer group. Based on the peer group, color image corrupted with mixed Gaussian and impulse noise is filtered. The novel method for filtering is an adaptive weighted average of different sized filters. The weights of different sized filters are adaptive to local noise and edge information. The proposed work has been compared with some state-of-the-art techniques. The results show proposed approach is better in preserving edge and color information than others. [ABSTRACT FROM AUTHOR]

The block-matching 3-D (BM3D) algorithm, based on the nonlocal approach, is one of the most effective methods to date for additive white Gaussian noise image denoising. Likewise, its extension to synthetic aperture radar (SAR) amplitude images, SAR-BM3D, is a state-of-the-art SAR despeckling algorithm. In this paper, we further extend BM3D to address the restoration of SAR interferometric phase images. While keeping the general structure of BM3D, its processing steps are modified to take into account the peculiarities of the SAR interferometry signal. Experiments on simulated and real-world Tandem-X SAR interferometric pairs prove the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

W-CDMA is radio access utilized for 3G cell frameworks. A code tree allocation scheme is one of the most explored channelization techniques, used to improve system performance and capacity through adjustable data rates. This work investigates the accuracy of bit error probability for WCDMA system using code tree orthogonal variable spreading factor (OVSF) codes, compared to pseudo-noise (PN) codes under various noise conditions, such as additive white Gaussian Noise (AWGN) and Random Noise (RN). Results are carried out theoretically and by computer simulation. The simulation includes the scenario of simple model representation for WCDMA system. It was concluded that, the system has better performance using OVSF compared with PN code under different noisy channels. [ABSTRACT FROM AUTHOR]

The key challenges in real time voice communication in long term evolution mobile are reduction in complexity and latency. Efficient encoding and decoding algorithms can cater to these. The implementation of such polar code based efficient algorithms is proposed in this paper. The overall latency of 3.8 ms is needed to process 8 bit block length. The novel sub-matrix near to identity matrix is presented. This resulted into minimization of loops among least reliable bits due to iterated parity check matrix. Look-up table based memory mapping is used in encoder to reduce latency while Euclidian decoding technique is used in decoder. The number of iterations is reduced by 50%. The experimentation is performed with additive white Gaussian noise and QPSK modulation. The proposed modified iterative decoding algorithm requires SNR of 5.5 dB and 192 computations for targeted bit error rate of 10. The second proposed method needs 9 dB, 2 iterations for 384 computations. The penalty paid is quantization error of 0.63% due to restricting computations to fourth order series of hyperbolic function with same 8 bit block length. [ABSTRACT FROM AUTHOR]

We propose a non-iterative image deconvolution algorithm for data corrupted by Poisson or mixed Poisson-Gaussian noise. Many applications involve such a problem, ranging from astronomical to biological imaging. We parameterize the deconvolution process as a linear combination of elementary functions, termed as linear expansion of thresholds. This parameterization is then optimized by minimizing a robust estimate of the true mean squared error, the Poisson unbiased risk estimate. Each elementary function consists of a Wiener filtering followed by a pointwise thresholding of undecimated Haar wavelet coefficients. In contrast to existing approaches, the proposed algorithm merely amounts to solving a linear system of equations, which has a fast and exact solution. Simulation experiments over different types of convolution kernels and various noise levels indicate that the proposed method outperforms the state-of-the-art techniques, in terms of both restoration quality and computational complexity. Finally, we present some results on real confocal fluorescence microscopy images and demonstrate the potential applicability of the proposed method for improving the quality of these images. [ABSTRACT FROM PUBLISHER]

A transmission scheme based on rateless codes is proposed for image delivery over additive white Gaussian noise (AWGN) channels. Unequal Error Protection (UEP) characteristics are also introduced to provide prioritized delivery for different layers in content-based image. Firstly, layer segmentation processing based on an improved guided filtering is introduced to decompose the source image into the base layer and detail layer. Then, a windowing technique is applied to produce a bias towards certain classes of layers according to their various protection requirements. Variable-node degree distribution is also exploited to provide enhanced UEP and improve the high error floor suffered by some conventional UEP schemes. Compared with the conventional image transmission schemes based on rateless codes with UEP, the additional parameters introduced by the proposed scheme make it more general and flexible for individual applications. Furthermore, the proposed approach can provide better UEP performance and improve the network image transmission quality, which are confirmed both theoretically and experimentally. [ABSTRACT FROM AUTHOR]

In this paper, we propose to derive an approximate theoretical distribution under the null hypothesis of the low-rank adaptive normalized matched filter (LR-ANMF). This detector is used to detect a target when the disturbance is composed of a low-rank Gaussian contribution (called clutter) and an additive white Gaussian noise. In the LR-ANMF, the estimated covariance matrix is replaced by the estimated orthogonal projector onto the subspace clutter. The method to derive this distribution is based on perturbation analysis and assumes a steering vector far from the clutter and a large clutter-to-noise ratio. Simulations on a space?time adaptive processing example validate our theoretical result. The impact of both hypotheses is also studied. [ABSTRACT FROM PUBLISHER]

Anytime transmission was previously shown to be necessary and sufficient for tracking and controlling an unstable plant over a noisy channel. In this paper, we propose an efficient channel coding scheme for anytime transmission. We design this coding scheme based on spatially coupled codes and investigate its performance over binary erasure channels (BEC) and binary input additive white Gaussian noise (BIAWGN) channels. Through density evolution analysis, we asymptotically show the desired anytime properties of the proposed code. For the BEC, we derive the corresponding delay-exponent and numerically predict the finite-length performance of the proposed anytime code. We also propose adaptive window decoding techniques to ensure low complexity anytime receivers. [ABSTRACT FROM PUBLISHER]

In this letter, a new subspace based estimator that can effectively provide the order and frequencies of multiple sinusoids in noise is proposed. The estimator, referred to as SAS-Est (Subspace Aligning and Separating Estimator), simultaneously seeks to separate the steering vectors from the noise subspace and align them to the signal subspace. The angles between subspaces and the generalized Kullback-Leibler divergence are used in characterizing the alignment and separation. Minimizing the divergence leads to maximal subspace separation and best alignment, thus allowing improved performance. Simulations in additive white Gaussian noise show that the new estimator offers an improvement for both model order and frequency estimation. When compared with other methods, the improvement is more pronounced for high model orders and low signal-to-noise ratio values. [ABSTRACT FROM AUTHOR]

Collaborative communication produces high power gain and significantly reduces bit error rate (BER) if both frequency and phase synchronization are achieved. In this paper, a novel collaborative communication system with imperfect phase and frequency synchronization that includes the influence of noise and fading is proposed, modeled, theoretically analyzed, and simulated. Mathematical expressions are derived for the received power as a function of number of collaborative nodes and BER as a function of signal to noise ratio ( E b ∕ N0). To analyze the energy efficiency of our proposed collaborative communication system, energy consumption of the system is modeled, simulated, and analyzed by considering the parameters of the off-the-shelf products. Analytical and simulation results showed that the proposed system produces significant power gain and reduction in BER in the presence of phase errors, frequency errors, additive white Gaussian noise, and Rayleigh fading. A detailed theoretical analysis and Monte Carlo simulation revealed that the proposed collaborative communication system is an energy efficient communication system that can be implemented in sensor networks, as approximately N (number of collaborative nodes) times less total transmitted power is required than for the single input single output communication for a specifies transmission range. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The ability to recognize various forms of contaminants in surface electromyography (EMG) signals and to ascertain the overall quality of such signals is important in many EMG-enabled rehabilitation systems. In this paper, new methods for the automatic identification of commonly occurring contaminant types in surface EMG signals are presented. Such methods are advantageous because the contaminant type is typically not known in advance. The presented approach uses support vector machines as the main classification system. Both simulated and real EMG signals are used to assess the performance of the methods. The contaminants considered include: 1) electrocardiogram interference; 2) motion artifact; 3) power line interference; 4) amplifier saturation; and 5) additive white Gaussian noise. Results show that the contaminants can readily be distinguished at lower signal to noise ratios, with a growing degree of confusion at higher signal to noise ratios, where their effects on signal quality are less significant. [ABSTRACT FROM AUTHOR]

Multidimensional lattice constellations which present signal space diversity (SSD) have been extensively studied for single-antenna transmission over fading channels, with focus on their optimal design for achieving high diversity gain. In this two-part series of papers we present a novel combinatorial geometrical approach based on parallelotope geometry, for the performance evaluation of multidimensional finite lattice constellations with arbitrary structure, dimension and rank. In Part I, we present an analytical expression for the exact symbol error probability (SEP) of multidimensional signal sets, and two novel closed-form bounds, named Multiple Sphere Lower Bound (MLSB) and Multiple Sphere Upper Bound (MSUB). Part II extends the analysis to the transmission over fading channels, where multidimensional signal sets are commonly used to combat fading degradation. Numerical and simulation results show that the proposed geometrical approach leads to bounds that can be used for the performance evaluation and the design of multidimensional lattice constellations, both in Additive White Gaussian Noise (AWGN) and fading channels. [ABSTRACT FROM PUBLISHER]

The focus of this paper is to study the performance of the quantize-and-forward (QF) scheme over a half-duplex relay channel that is slowly fading, with the assumption that the channel state information (CSI) is available only at the receiver side. In order to do so, three steps are taken. The first step is to characterize the achievable rate of the QF scheme over a discrete memoryless half-duplex relay channel. Then, the achievable rate over a corresponding additive white Gaussian noise channel is obtained (the specific assumption regarding the CSI in this paper makes this step nontrivial). With the results from the first two steps, performance measures such as outage probability, expected rate, and diversity-multiplexing tradeoff (DMT) over slow fading channels are evaluated. It is shown that the QF scheme can significantly outperform the compress-and-forward scheme at finite signal-to-noise ratio (SNR) and it can achieve the optimal DMT at asymptotically high SNR. Moreover, it is shown that simple feedback from the destination node to the relay node can further improve the performance of the QF scheme. [ABSTRACT FROM AUTHOR]

We consider the problem of jointly optimum modulation and estimation of a real-valued random parameter, conveyed over an additive white Gaussian noise (AWGN) channel, where the performance metric is the large deviations behavior of the estimator, namely the exponential decay rate (as a function of the observation time) of the probability that the estimation error would exceed a certain threshold. Our basic result is in providing an exact characterization of the fastest achievable exponential decay rate, among all possible modulator–estimator (transmitter-receiver) pairs, where the modulator is limited only in the signal power, but not in bandwidth. This exponential rate turns out to be given by the reliability function of the AWGN channel. We also discuss several ways to achieve this optimum performance, and one of them is based on quantization of the parameter, followed by optimum channel coding and modulation, which gives rise to a separation-based transmitter, if one views this setting from the perspective of joint source-channel coding. This is in spite of the fact that, in general, when error exponents are considered, the source-channel separation theorem does not hold true. We also discuss several observations, modifications, and extensions of this result in several directions, including other channels, and the case of multidimensional parameter vectors. One of our findings concerning the latter is that there is an abrupt threshold effect in the dimensionality of the parameter vector: below a certain critical dimension, the probability of excess estimation error may still decay exponentially, but beyond this value, it must converge to unity. [ABSTRACT FROM AUTHOR]

This paper compares the partial-decode-forward and the complete-decode-forward coding strategies for the half-duplex Gaussian single-relay channel. We analytically show that the rate achievable by partial-decode-forward outperforms that of the more straightforward complete-decode-forward by at most 12.5%. Furthermore, in the following asymptotic cases, the gap between the partial-decode-forward and the complete-decode-forward rates diminishes: (i) when the relay is close to the source, (ii) when the relay is close to the destination, and (iii) when the SNR is low. In addition, when the SNR increases, this gap, when normalized to the complete-decode-forward rate, also diminishes. Consequently, significant performance improvements are not achieved by optimizing the fraction of data the relay should decode and forward, over simply decoding the entire source message. [ABSTRACT FROM AUTHOR]

The conventional additive white Gaussian noise (AWGN) model adequately simulates many noisy environments that hamper the performance of practical digital communication systems. However if the channel noise is impulsive, the approximation this model provides reduces significantly. The AWGN channel may then be replaced by the more general additive white symmetric α-stable noise (AWSαSN) model. When converted to its complex baseband form, the resulting noise for the non-Gaussian AWSαSN case is radically different from its Gaussian counterpart. In this paper we investigate the properties of baseband noise for the general AWSαSN case using conventional passband-to-baseband conversion schemes. The converted noise is generally not isotropic and furthermore the real and imaginary components may be dependent. By varying certain physical parameters we may attain different non-isotropic distributions. Using the variable geometry offered by these distributions, efficient placement of signal points on the constellation map for the quadrature phase-shift keying (QPSK) scheme is proposed. It is shown that efficient placement of signal points significantly improve the uncoded error performance of the system. We plot the bit error rate (BER) and symbol error rate (SER) curves against a signal-to-noise ratio (SNR) measure for a few selected rotated versions of the QPSK scheme. [ABSTRACT FROM PUBLISHER]

In energy harvesting communication systems, an exogenous recharge process supplies energy necessary for data transmission and the arriving energy can be buffered in a battery before consumption. We determine the information-theoretic capacity of the classical additive white Gaussian noise (AWGN) channel with an energy harvesting transmitter with an unlimited sized battery. As the energy arrives randomly and can be saved in the battery, codewords must obey cumulative stochastic energy constraints. We show that the capacity of the AWGN channel with such stochastic channel input constraints is equal to the capacity with an average power constraint equal to the average recharge rate. We provide two capacity achieving schemes: save-and-transmit and best-effort-transmit. In the save-and-transmit scheme, the transmitter collects energy in a saving phase of proper duration that guarantees that there will be no energy shortages during the transmission of code symbols. In the best-effort-transmit scheme, the transmission starts right away without an initial saving period, and the transmitter sends a code symbol if there is sufficient energy in the battery, and a zero symbol otherwise. Finally, we consider a system in which the average recharge rate is time varying in a larger time scale and derive the optimal offline power policy that maximizes the average throughput, by using majorization theory. [ABSTRACT FROM PUBLISHER]

In this correspondence, a computationally efficient method that combines the subspace and projection separation approaches is developed for R -dimensional (R-D) frequency estimation of multiple sinusoids, where R ≥ 3, in the presence of white Gaussian noise. Through extracting a 2-D slice matrix set from the multidimensional data, we devise a covariance matrix associated with one dimension, from which the corresponding frequencies are estimated using the root-MUSIC method. With the use of the frequency estimates in this dimension, a set of projection separation matrices is then constructed to separate all frequencies in the remaining dimensions. Root-MUSIC method is again applied to estimate these single-tone frequencies while multidimensional frequency pairing is automatically attained. Moreover, the mean square error of the frequency estimator is derived and confirmed by computer simulations. It is shown that the proposed approach is superior to two state-of-the-art frequency estimators in terms of accuracy and computational complexity. [ABSTRACT FROM PUBLISHER]

In this paper, parameter estimation for R-dimensional (R -D) sinusoids with R >; 2 in additive white Gaussian noise is addressed. With the use of tensor algebra and principal-singular-vector utilization for modal analysis, the sinusoidal parameters at one dimension are first accurately estimated according to an iterative procedure which utilizes the linear prediction property and weighted least squares. The damping factors and frequencies in the remaining dimensions are then solved such that pairing of the R-D parameters is automatically achieved. Algorithm modification for a single R -D tone is made and it is proved that the frequency estimates are asymptotically unbiased while their variances approach Cramér-Rao lower bound at sufficiently high signal-to-noise ratio conditions. Computer simulations are also included to compare the proposed approach with conventional R -D harmonic retrieval schemes in terms of mean square error performance and computational complexity. [ABSTRACT FROM PUBLISHER]

The L-user additive white Gaussian noise multiway relay channel is investigated, where L users exchange information at the same rate through a single relay. A new achievable rate region, based on the functional-decode-forward coding strategy, is derived. For the case where there are three or more users, and all nodes transmit at the same power, the capacity is obtained. For the case where the relay power scales with the number of users, it is shown that both compress-forward and functional-decode-forward achieve rates within a constant number of bits of the capacity at all SNR levels; in addition, functional-decode-forward outperforms compress-forward and complete-decode-forward at high SNR levels. [ABSTRACT FROM AUTHOR]

This paper studies classes of generic deterministic, discrete time, memoryless, and “nonlinear” additive white Gaussian noise (AWGN) channels. Subject to multiple types of constraints such as the even-moment and compact-support constraints or a mixture, the optimal input is proved to be discrete with finite number of mass points in the vast majority of the cases. Only under the even-moment constraint and for special cases that emulate the average power constrained linear channel, capacity is found to be achieved by an absolutely continuous input. The results are extended to channels where the distortion is generally piecewise nonlinear where the discrete nature of the optimal input is conserved. These results are reached through the development of methodology and tools that are based on standard decompositions in a Hilbert space with the Hermite polynomials as a basis, and it is showcased how these bases are natural candidates for general information-theoretic studies of the capacity of channels affected by AWGN. Intermediately, novel results regarding the output rate of decay of Gaussian channels are derived. Namely, the output probability distribution of any channel subjected to additive Gaussian noise decays necessarily “slower” than the Gaussian itself. Finally, numerical computations are provided for some sample cases, optimal inputs are determined, and capacity curves are drawn. These results put into question the accuracy of adopting the widely used expression 1\over2\log(1+\ssr SNR) for computing capacities of Gaussian deterministic channels. [ABSTRACT FROM PUBLISHER]

A code for communication over the k-receiver complex additive white Gaussian noise broadcast channel (BC) with feedback is presented and analyzed using tools from the theory of linear quadratic Gaussian optimal control. It is shown that the performance of this code depends on the noise correlation at the receivers and it is related to the solution of a discrete algebraic Riccati equation. For the case of independent noises, the sum rate achieved by the proposed code, satisfying average power constraint P, is characterized as 1/2 \log (1+P\phi), where the coefficient \phi \in [1,k] quantifies the power gain due to the presence of feedback. This includes a previous result by Elia and strictly improves upon the codes by Ozarow and Leung and by Kramer. When the noises are correlated, the prelog of the sum capacity of the BC with feedback can be strictly greater than 1. It is established that for all noise covariance matrices of rank r the prelog of the sum capacity is at most k-r+1 and, conversely, there exists a noise covariance matrix of rank r for which the proposed code achieves this upper bound. This generalizes a previous result by Gastpar et al. for the two-receiver BC. [ABSTRACT FROM PUBLISHER]

The Bayesian parameter estimation problem using a single-bit dithered quantizer is considered. This problem arises, e.g., for channel estimation under low-precision analog-to-digital conversion (ADC) at the receiver. Based on the Bayesian Cramér-Rao lower bound (CRLB), bounds on the mean squared error are derived that hold for all dither strategies with strictly causal adaptive processing of the quantizer output sequence. In particular, any estimator using the binary quantizer output sequence is asymptotically (in the sequence length) at least 10\log10(\pi/2)\approx 1.96 dB worse than the minimum mean squared error estimator using continuous observations, for any dither strategy. Moreover, dither strategies are designed that are shown by simulation to closely approach the derived lower bounds. [ABSTRACT FROM AUTHOR]

In this paper, we derive new exact and general expressions for the symbol error rate (SER) and bit error rate (BER) of M-ary \theta-quadrature amplitude modulation (QAM) for M = \2^l, l \geq \4, based on not only square-QAM (SQAM) for M = \2^2l, l \geq \2 but cross-QAM (CQAM) as well, for M = \2^2l + 1, l \geq \2 in additive white Gaussian noise (AWGN) and various fading channels; we also present the optimum angle and constellation of M-ary \theta-QAM. Through computer simulations, we confirm the results of the theoretical analysis. Because the SER and BER expressions are provided in terms of 2-D Gaussian Q -function in AWGN and various fading channels, they will be very useful for numerical evaluations in various cases of practical interest in QAM systems. [ABSTRACT FROM PUBLISHER]

Asymptotic comparisons of ergodic channel capacity at high and low SNRs are provided for several adaptive transmission schemes over fading channels with general distributions, including optimal power and rate adaptation, rate adaptation only, channel inversion and its variants. Analysis of the high-SNR pre-log constants of the ergodic capacity reveals the existence of constant capacity difference gaps among the schemes with a pre-log constant of 1. Closed-form expressions for these high-SNR capacity difference gaps are derived, which are proportional to the SNR loss between these schemes in dB scale. The largest one of these gaps is found to be between the optimal power and rate adaptation scheme and the channel inversion scheme. Based on these expressions it is shown that the presence of space diversity or multi-user diversity makes channel inversion arbitrarily close to achieving optimal capacity at high SNR with sufficiently large number of antennas or users. A low-SNR analysis also reveals that the presence of fading provably always improves capacity at sufficiently low SNR, compared to the additive white Gaussian noise (AWGN) case. Numerical results are shown to corroborate our analytical results. [ABSTRACT FROM AUTHOR]

A new approach for image matting is proposed based on the Kalman filter, to extract the matte and original foreground, despite the presence of noise in the observed image. Different filter formulations with a discontinuity-adaptive Markov random field prior are proposed for handling additive white Gaussian noise and film-grain noise. [ABSTRACT FROM AUTHOR]

A simple and straightforward method of constructing higher-level three-dimensional (3-D) signal constellations for a reliable digital communication system is proposed in this paper. The new method expands basic 8-ary constellation into 3-D signal space systematically so that it produces lattice configurations. We also derive accurate closed-form symbol error probability (SEP) of cross-lattice constellations in additive white Gaussian noise (AWGN). It is verified that the theoretical SEPs are almost the same as simulation results. Minimum Euclidean distance (MED) of the higher-level 3-D constellations is increased at least 49% in comparison with quadrature amplitude modulation (QAM). When the number of symbols is 256, the 3-D constellation has around 105% longer MED than the 2-D QAM. Due to increase in MED, the 3-D constellations have much improved error performance compared to the QAM configurations. It is, therefore, considered that the higher-level 3-D constellations are appropriate for high-quality digital communications. [ABSTRACT FROM AUTHOR]

A robust coded scheme for progressive multimedia transmission is proposed for additive white Gaussian noise, flat Rayleigh fading channels, and frequency-selective channels using different unequal error protection methods in combination. Hierarchical modulation is coupled with a packetization/combining strategy and an efficient channel encoder consisting of a cyclic redundancy check outer coder concatenated with an inner rate-compatible punctured convolutional coder. Distortion-optimal hierarchical parameters are jointly chosen with the set of channel coding parameters on a packet-switched wireless network with fixed length packets. A lower bound for the performance improvement of the proposed system is derived and shown to give significant gains at lower packet sizes and higher transmission rates. The proposed system is also shown to outperform several existing schemes for realistic wireless channels. [ABSTRACT FROM PUBLISHER]

Orthogonal frequency-division multiplexing (OFDM) systems usually make use of a set of square M quadrature-amplitude modulation ( M-QAM) constellations to obtain a good tradeoff between throughput and symbol-error robustness. However, the switch to the next constellation increases the number of bits per modulation symbol by two. The introduction of nonsquare M -QAM constellations in such systems brings extra advantages such as smoother transition among bit rates and a reduction of the peak-to-average ratio of the OFDM signal. Therefore, this paper unfolds analytical expressions to evaluate the symbol-error performance of nonsquare M-QAM OFDM on nonlinear time-variant additive white Gaussian noise channels, taking clipping distortion into account. Cross and overlaid M-QAM are considered. Analytical performances are evaluated and compared with computational simulations, which show good agreement. [ABSTRACT FROM PUBLISHER]

Suppressing intertrack interference (ITI) and intersymbol interference (ISI) is crucial for achieving high-density magnetic recording beyond 10 Tera bits/inch^2. We propose a novel iterative method for reducing errors caused by ITI and ISI involving the adaptive estimation of ITI and the log likelihood ratios obtained from signals of neighboring tracks. This method is useful for decoding signals recorded by bit-patterned media and conventional media. Moreover, the method is extended to decode signals from the Voronoi-based discrete grain model for shingled write recording (SWR), accounting for four neighboring bits. Bit errors due to both neighboring track shifts of approximately 20% can be canceled for BPM and SWR. [ABSTRACT FROM AUTHOR]

This paper proposes a method for localizing homogeneity and estimating additive white Gaussian noise (AWGN) variance in images. The proposed method uses spatially and sparsely scattered initial seeds and utilizes particle filtering techniques to guide their spatial movement towards homogeneous locations. This way, the proposed method avoids the need to perform the full search associated with block-based noise estimation methods. To achieve this, the paper proposes for the particle filter a dynamic model and a homogeneity observation model based on Laplacian structure detectors. The variance of AWGN is robustly estimated from the variances of blocks in the detected homogeneous areas. A proposed adaptive trimmed-mean based robust estimator is used to account for the reduction in estimation samples from the full search approach. Our results show that the proposed method reduces the number of homogeneity measurements required by block-based methods while achieving more accuracy. [ABSTRACT FROM AUTHOR]

We present an exact analysis of the correlation coefficient, in the frequency domain, between the real and imaginary parts of the impulse noise squared norms for OFDM systems. We analyze a scenario where M Gaussian randomly positioned impulses interfere the OFDM signal, with and without the presence of a background thermal noise. Variability of M is taken into account through the Bernoulli–Gauss model. We demonstrate that rather high correlation values occur with not negligible probabilities under certain operation conditions. This has an impact on the design of impulse noise suppression techniques as well as on the error rate performance. [ABSTRACT FROM PUBLISHER]

In broadband wireless communication systems, orthogonal frequency division multiplexing (OFDM) will suffer from severe performance degradation in the presence of phase noise (PHN) especially for the applications with narrow subcarrier spacing to support high bit rate. In the Chinese digital television terrestrial multimedia broadcasting (DTMB) system the time-domain synchronous OFDM (TDS-OFDM) is adopted in which the time-domain pseudo noise (PN) sequences and OFDM data block are combined into a signal frame. Continuous transmission parameter signaling (TPS) symbols are inserted into OFDM data blocks in the frequency domain which can be used for phase noise estimation. In this paper, joint channel estimation and phase noise reduction algorithms are investigated for DTMB systems using the common phase error (CPE) of PN sequences as an intermediate variable of channel frequency response (CFR) during estimation stage and removing it at compensation stage. A simplified channel and phase noise equalization method performed in both frequency and time domain is studied to suppress the distortion. Simulations prove that this proposed scheme has low complexity and works well under additive white Gaussian noise (AWGN) and multipath fading channels. [ABSTRACT FROM PUBLISHER]

We propose a general methodology (PURE-LET) to design and optimize a wide class of transform-domain thresholding algorithms for denoising images corrupted by mixed Poisson–Gaussian noise. We express the denoising process as a linear expansion of thresholds (LET) that we optimize by relying on a purely data-adaptive unbiased estimate of the mean-squared error (MSE), derived in a non-Bayesian framework (PURE: Poisson–Gaussian unbiased risk estimate). We provide a practical approximation of this theoretical MSE estimate for the tractable optimization of arbitrary transform-domain thresholding. We then propose a pointwise estimator for undecimated filterbank transforms, which consists of subband-adaptive thresholding functions with signal-dependent thresholds that are globally optimized in the image domain. We finally demonstrate the potential of the proposed approach through extensive comparisons with state-of-the-art techniques that are specifically tailored to the estimation of Poisson intensities. We also present denoising results obtained on real images of low-count fluorescence microscopy. [ABSTRACT FROM AUTHOR]

In this paper we engage in AWGN watermark for grayscale image (the message is embedded by adding of white Gaussian noise matrix; detection is blind, correlation based). We search criteria for "the best" (minimal one which guaranties watermark detectability) embedding strength for watermark robust against expected attack. These criteria we find for AWGN watermarks, which are embedded in spatial or in transform domains; for one bit message or for a longer message; into whole image or into some of its coefficients. This paper peculiarity is that we do not propose new watermarking algorithm; for well known, robust algorithm we find the best embedding strength for robust watermark. [ABSTRACT FROM AUTHOR]

We present a novel iterative algorithm for detection of binary Markov random fields (MRFs) corrupted by 2-D intersymbol interference (ISI) and additive white Gaussian noise. We assume a first-order binary MRF as a simple model for correlated images. We assume a 2-D digital storage channel, where the MRF is interleaved before being written and then read by a 2-D transducer; such channels occur in recently proposed optical disk storage systems. The detection algorithm is a concatenation of two soft-input/soft-output (SISO) detectors: an iterative row-column soft-decision feedback (IRCSDF) ISI detector, and a MRF detector. The MRF detector is a SISO version of the stochastic relaxation algorithm by Geman and Geman. On the 2times2 averaging-mask ISI channel, at a bit error rate of 10-4, the concatenated algorithm achieves SNR savings of between 0.2 and 2.0 dB over the IRCSDF detector alone; the savings increase as the MRFs become more correlated, or as the SNR decreases. The algorithm is also fairly robust to mismatches between the assumed and actual MRF parameters. [ABSTRACT FROM PUBLISHER]

In 2017, Polyanskiy showed that the trade-off between power and bandwidth efficiency for massive Gaussian random access is governed by two fundamentally different regimes: low power and high power. For both regimes, tight performance bounds were found by Zadik et al., in 2019. This work utilizes recent results on the exact block error probability of Gaussian random codes in additive white Gaussian noise to propose practical methods based on iterative soft decoding to closely approach these bounds. In the low power regime, this work finds that orthogonal random codes can be applied directly. In the high power regime, a more sophisticated effort is needed. This work shows that power-profile optimization by means of linear programming, as pioneered by Caire et al. in 2001, is a promising strategy to apply. The proposed combination of orthogonal random coding and iterative soft decoding even outperforms the existence bounds of Zadik et al. in the low power regime and is very close to the non-existence bounds for message lengths around 100 and above. Finally, the approach of power optimization by linear programming proposed for the high power regime is found to benefit from power imbalances due to fading which makes it even more attractive for typical mobile radio channels. [ABSTRACT FROM AUTHOR]

This paper gives a detailed performance analysis for the novel radar long-time coherent integration method, i.e., Radon-Fourier transforms (RFT). Some important properties of RFT, e.g., two-dimensional (2D) impulse response, 2D translational invariance, multitarget linear additivity, linear signal-to-noise ratio gain in additive white Gaussian noise (AWGN), as well as the 2D correlation function of transformed AWGN, are derived for continuous and discrete RFT, respectively. However, because of discrete pulse sampling, finite range resolution, and limited integration time, the "blind-speed sidelobes (BSSL)" of discrete RFT may inevitably appear in real applications. Although the BSSL are reduced with the increase of the blind-speed integer, they may still lead to false alarms or loss detections in a real multitarget scenario. Based on the analytic expression derived for BSSL, the causes of BSSL are analyzed and the effective BSSL suppression methods are proposed. Finally, numerical experiments are also provided to demonstrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

An adaptive nonlocal-means (ANL-means) algorithm for image denoising is proposed in this work. It employs the singular value decomposition (SVD) method and the K-means clustering (K-means) technique to achieve robust block classification in noisy images. Then, a local window is adaptively adjusted to match the local property of a block and a rotated matching algorithm that aligns the dominant orientation of a local region is adopted for similarity matching. Furthermore, the noise level is estimated using the block classification result and the Laplacian operator. Experimental results are given to demonstrate the superior denoising performance of the proposed ANL-means denoising technique over various image denoising benchmarks in terms of the PSNR value and perceptual quality comparison, where images corrupted by additive white Gaussian noise (AWGN) are tested. [ABSTRACT FROM AUTHOR]