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Signal Processing Letters, IEEE

Issue 1 • Date Jan. 2011

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Displaying Results 1 - 25 of 27
  • [Front cover]

    Publication Year: 2011 , Page(s): C1
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  • IEEE Signal Processing Letters publication information

    Publication Year: 2011 , Page(s): C2
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  • Table of contents

    Publication Year: 2011 , Page(s): 1 - 2
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  • Annealed SMC Samplers for Nonparametric Bayesian Mixture Models

    Publication Year: 2011 , Page(s): 3 - 6
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (146 KB) |  | HTML iconHTML  

    We develop a novel online algorithm for posterior inference in Dirichlet Process Mixtures (DPM). Our method is based on the Sequential Monte Carlo (SMC) samplers framework that generalizes sequential importance sampling approaches. Unlike the existing methods, the framework enables us to retrospectively update long trajectories in the light of recent observations and this leads to sophisticated clustering update schemes and annealing strategies that seem to prevent the algorithm to get stuck around a local mode. The performance has been evaluated on a Bayesian Gaussian density estimation problem with an unknown number of mixture components. Our simulations suggest that the proposed annealing strategy outperforms conventional samplers. It also provides significantly smaller Monte Carlo standard error with respect to particle filtering given comparable computational resources. View full abstract»

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  • Mean Weight Behavior of the NLMS Algorithm for Correlated Gaussian Inputs

    Publication Year: 2011 , Page(s): 7 - 10
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (228 KB) |  | HTML iconHTML  

    This letter presents a novel approach for evaluating the mean behavior of the well known normalized least mean squares (NLMS) adaptive algorithm for a circularly correlated Gaussian input. The mean analysis of the NLMS algorithm requires the calculation of some normalized moments of the input. This is done by first expressing these moments in terms of ratios of quadratic forms of spherically symmetric random variables and finding the cumulative density function (CDF) of these variables. The CDF is then used to calculate the required moments. As a result, we obtain explicit expressions for the mean behavior of the NLMS algorithm. View full abstract»

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  • Computationally Efficient Approaches to Aeroacoustic Source Power Estimation

    Publication Year: 2011 , Page(s): 11 - 14
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (261 KB) |  | HTML iconHTML  

    Two computationally efficient approaches are proposed for aeroacoustic source power estimation, under the assumption of a single dominant source contaminated by uncorrelated noise. The proposed methods are evaluated using both simulated and measured data. The numerical examples show that the proposed algorithms yield good power estimates even under low signal-to-noise ratio (SNR) conditions, and the experimental results show that the power estimates obtained via the proposed approaches are consistent with each other. Furthermore, the approaches are computationally much more efficient than the existing nonlinear least-squares (NLS) algorithm. View full abstract»

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  • Channel Access Allocation for Scalable Video Transmission Over Contention-Based Wireless Networks

    Publication Year: 2011 , Page(s): 15 - 18
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (200 KB) |  | HTML iconHTML  

    Contention-based wireless networks make use of random access delay in the medium access control (MAC) layer to share the channel efficiently among users. This channel access scheme poses challenges to video traffic which is delay-sensitive. When channel access is limited, how to optimally allocate channel access and judiciously drop video packets remains an open issue. In this paper, we investigate the optimal channel access allocation and preemptive packet drop strategy for scalable video packets using contention-based MAC. We first establish a relationship to associate the characteristics of video packets, the cumulative distribution function of channel access delays and the expected video quality at the receiver. Based on the relationship, we define a video utility function that explicitly takes into account cumulative distribution of channel access delay over contention-based wireless links, video packet length and truncation, packet loss rate and quality impacts of SVC layers. As the analytical model of the video utility function is rather complex for optimization, we further propose an approximation model for the video utility function to transform the optimization problem into a convex problem which is a solvable by using the dual decomposition method. Simulation results confirm that our proposed method achieves better PSNR performance over the existing approach, especially when the total channel access for the video traffic is limited. View full abstract»

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  • Binocular Just-Noticeable-Difference Model for Stereoscopic Images

    Publication Year: 2011 , Page(s): 19 - 22
    Cited by:  Papers (13)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (387 KB) |  | HTML iconHTML  

    Conventional 2-D Just-Noticeable-Difference (JND) models measure the perceptible distortion of visual signal based on monocular vision properties by presenting a single image for both eyes. However, they are not applicable for stereoscopic displays in which a pair of stereoscopic images is presented to a viewer's left and right eyes, respectively. Some unique binocular vision properties, e.g., binocular combination and rivalry, need to be considered in the development of a JND model for stereoscopic images. In this letter, we propose a binocular JND (BJND) model based on psychophysical experiments which are conducted to model the basic binocular vision properties in response to asymmetric noises in a pair of stereoscopic images. The first experiment exploits the joint visibility thresholds according to the luminance masking effect and the binocular combination of noises. The second experiment examines the reduction of visual sensitivity in binocular vision due to the contrast masking effect. Based on these experiments, the developed BJND model measures the perceptible distortion of binocular vision for stereoscopic images. Subjective evaluations on stereoscopic images validate of the proposed BJND model. View full abstract»

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  • Shadow Compensation Using Fourier Analysis With Application to Face Recognition

    Publication Year: 2011 , Page(s): 23 - 26
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (656 KB) |  | HTML iconHTML  

    Shadows that occur on face images due to illumination variation can change the appearance of a face and degrade face recognition performance. In this paper, we propose a new shadow compensation method based on the Fourier analysis for handling illumination variation. The face image deteriorated by shadow is restored by using the auxiliary magnitude, which compensates for the magnitude of the Fourier transform distorted due to the illumination variation. The experimental results for the CMU-PIE and Yale B databases show that the proposed method results in improved recognition performance under illumination variation. View full abstract»

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  • Stepwise Optimal Subspace Pursuit for Improving Sparse Recovery

    Publication Year: 2011 , Page(s): 27 - 30
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (260 KB) |  | HTML iconHTML  

    We propose a new iterative algorithm to reconstruct an unknown sparse signal x from a set of projected measurements y = Φx . Unlike existing methods, which rely crucially on the near orthogonality of the sampling matrix Φ , our approach makes stepwise optimal updates even when the columns of Φ are not orthogonal. We invoke a block-wise matrix inversion formula to obtain a closed-form expression for the increase (reduction) in the L2-norm of the residue obtained by removing (adding) a single element from (to) the presumed support of x . We then use this expression to design a computationally tractable algorithm to search for the nonzero components of x . We show that compared to currently popular sparsity seeking matching pursuit algorithms, each step of the proposed algorithm is locally optimal with respect to the actual objective function. We demonstrate experimentally that the algorithm significantly outperforms conventional techniques in recovering sparse signals whose nonzero values have exponentially decaying magnitudes or are distributed N(0,1) . View full abstract»

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  • A Testbed and Methodology for Comparing Live Video Frame Rate Control Methods

    Publication Year: 2011 , Page(s): 31 - 34
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (276 KB) |  | HTML iconHTML  

    Most existing methods for video frame rate control were developed for prerecorded video. With the proliferation of mobile audiovisual communication devices, it is becoming important to develop frame rate control methods for live (i.e., not prerecorded) video as well. In this letter, we present a testbed and the corresponding methodology suitable for comparing such methods. We illustrate the methodology and the use of the testbed through comparison of an existing state-of-the-art frame rate control method against a simple new control method developed specifically for live video. View full abstract»

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  • Wideband Spectrum Sensing for Cognitive Radios With Correlated Subband Occupancy

    Publication Year: 2011 , Page(s): 35 - 38
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (284 KB) |  | HTML iconHTML  

    In this letter, we consider wideband spectrum sensing in the presence of correlation between the occupancies of frequency subbands. We begin by formulating the maximum a posteriori (MAP) estimator of channel occupancy based on measurements from multiple frequency subbands. Since the MAP estimator's complexity grows exponentially with the number of subbands, we propose an alternative structure, in which the subband energy measurements are linearly combined according to a minimum mean-square error (MMSE) criterion to form a sufficient statistic for binary detection in each subband. Through analysis and numerical simulations, we show that the proposed frequency-coupled detector can significantly outperform the traditional decoupled one. View full abstract»

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  • Security Analysis on Spatial \pm 1 Steganography for JPEG Decompressed Images

    Publication Year: 2011 , Page(s): 39 - 42
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (573 KB) |  | HTML iconHTML  

    Although many existing steganalysis works have shown that the spatial ±1 steganography on JPEG pre-compressed images is relatively easier to be detected compared with that on the never-compressed images, most experimental results seem not very convincing since these methods usually assume that the quantization table of the JPEG stegos previously used is known before detection and/or the length of embedded message is fixed. Furthermore, there are just few effective quantitative algorithms for further estimating the spatial modifications. In this letter, we firstly propose an effective method to detect the quantization table from the contaminated digital images which are originally stored as JPEG format based on our recently developed work about JPEG compression error analysis , and then we present a quantitative method to reliably estimate the length of spatial modifications in those gray-scale JPEG stegos by using data fitting technology. The extensive experimental results show that our estimators are very effective, and the order of magnitude of prediction error can remain around measured by the mean absolute difference. View full abstract»

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  • Kronecker Product Based Second Order Approximation of Mean Value and Covariance Matrix in Nonlinear Transformations

    Publication Year: 2011 , Page(s): 43 - 46
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (138 KB) |  | HTML iconHTML  

    This paper derives new formulae for the approximations of the mean value and the covariance matrix of a random vector which is derived as a nonlinear transformation of another random vector. Towards this purpose, it is first proposed to formulate the Taylor series expansion by using Kronecker product operators along with partial derivatives block matrices. This formulation facilitates the mathematical manipulation of higher order terms in multidimensional systems. The final expressions for the mean value and covariance matrix are simple in block matrix notation, convenient and easy to implement. The analytical expressions are evaluated and verified in a typical nonlinear transformation faced in navigation systems. View full abstract»

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  • A Quaternion Gradient Operator and Its Applications

    Publication Year: 2011 , Page(s): 47 - 50
    Cited by:  Papers (24)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (160 KB) |  | HTML iconHTML  

    Real functions of quaternion variables are typical cost functions in quaternion valued statistical signal processing, however, standard differentiability conditions in the quaternion domain do not permit direct calculation of their gradients. To this end, based on the isomorphism with real vectors and the use of quaternion involutions, we introduce the HR calculus as a convenient way to calculate derivatives of such functions. It is shown that the maximum change of the gradient is in the direction of the conjugate gradient, which conforms with the corresponding solution in the complex domain. Examples in some typical gradient based optimization settings support the result. View full abstract»

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  • Visual Tracking Using High-Order Particle Filtering

    Publication Year: 2011 , Page(s): 51 - 54
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (251 KB) |  | HTML iconHTML  

    In this letter, we extend the first-order Markov chain model commonly used in visual tracking and present a novel framework of visual tracking using high-order Monte Carlo Markov chain. By using graphical models to obtain conditional independence properties, we derive a general expression for the posterior density function of an m th-order hidden Markov model. We subsequently use Sequential Importance Sampling (SIS) to estimate the posterior density and obtain the high-order particle filtering algorithm for visual object tracking. Experimental results demonstrate that the performance of our proposed algorithm is superior to traditional first-order particle filtering (i.e., particle filtering derived based on first-order Markov chain). View full abstract»

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  • Nearest Feature Space Analysis for Classification

    Publication Year: 2011 , Page(s): 55 - 58
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (149 KB) |  | HTML iconHTML  

    We propose in this letter two new subspace learning methods, called nearest feature space analysis (NFSA) and discriminant nearest feature space analysis (DNFSA), for pattern classification. While many subspace learning algorithms have been proposed in recent years, most of them apply the conventional nearest neighbor (NN) metric to derive the subspace and may not effectively characterize the geometrical information of the samples, especially when the number of training samples per class is limited. In this paper, we propose using the nearest feature space (NFS) metric to seek a NFSA subspace to improve the discriminating power of the subspace for classification. To further enhance the discriminative power of NFSA, we also propose a new DNFSA method to minimize the within-class feature space (FS) distances and maximize the between-class FS distances simultaneously in the derived subspace. Experimental results on face and facial expression recognition are presented to demonstrate the efficacy of the proposed methods. View full abstract»

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  • A Nuclear Norm Heuristic Approach to Fractionally Spaced Blind Channel Equalization

    Publication Year: 2011 , Page(s): 59 - 62
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (226 KB) |  | HTML iconHTML  

    This letter proposes an algorithm for the blind fractionally spaced equalization (FSE). We show that the rank minimization approach leads to the reduction of degrees of freedom in the blind FSE problem and improves the quality of equalization. By introducing the nuclear norm heuristic, the design problem of blind channel equalization is formulated as the nuclear norm minimization problem. We also show that the effect of noise is reduced by minimizing the nuclear norm. Numerical examples demonstrate the effectiveness of the proposed algorithm. View full abstract»

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  • Existence of Binary Z -Complementary Pairs

    Publication Year: 2011 , Page(s): 63 - 66
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (112 KB) |  | HTML iconHTML  

    The conventional binary complementary pairs exist only for very limited lengths, while binary Z -complementary pairs exist for many more lengths. In this letter, an upper bound on zero correlation zone (ZCZ) width of binary Z-complementary pairs of odd length is established. The existence conjecture of binary Z-complementary pairs with ZCZ widths 2, 3, 4, 5 and 6 is completely solved, and a new recursive construction of binary Z-complementary pairs is proposed. View full abstract»

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  • Performance Analysis of Relay Selection With Feedback Delay and Channel Estimation Errors

    Publication Year: 2011 , Page(s): 67 - 70
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (214 KB) |  | HTML iconHTML  

    In this letter, we investigate the effect of feedback delay and channel estimation errors in a decode-and-forward (DF) cooperative network with relay selection. In particular, we consider a multirelay cooperative scenario, where the best relay is selected from a subset of relays that are able to decode the source information correctly. In the selection scenario, the destination terminal estimates the relay-to-destination (R → D) channel state information (CSI) and sends the index of the best relay to the relay terminals via a delayed feedback link. We investigate the performance of the considered scenario in terms of average symbol error rate (ASER) and asymptotic diversity order. Simulation results are presented to corroborate the analytical results. View full abstract»

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  • A Modified SRP-PHAT Functional for Robust Real-Time Sound Source Localization With Scalable Spatial Sampling

    Publication Year: 2011 , Page(s): 71 - 74
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (393 KB) |  | HTML iconHTML  

    The Steered Response Power - Phase Transform (SRP-PHAT) algorithm has been shown to be one of the most robust sound source localization approaches operating in noisy and reverberant environments. However, its practical implementation is usually based on a costly fine grid-search procedure, making the computational cost of the method a real issue. In this letter, we introduce an effective strategy that extends the conventional SRP-PHAT functional with the aim of considering the volume surrounding the discrete locations of the spatial grid. As a result, the modified functional performs a full exploration of the sampled space rather than computing the SRP at discrete spatial positions, increasing its robustness and allowing for a coarser spatial grid. To this end, the Generalized Cross-Correlation (GCC) function corresponding to each microphone pair must be properly accumulated according to the defined microphone setup. Experiments carried out under different acoustic conditions confirm the validity of the proposed approach. View full abstract»

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  • Inpainting by Joint Optimization of Linear Combinations of Exemplars

    Publication Year: 2011 , Page(s): 75 - 78
    Cited by:  Papers (10)
    Multimedia
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (470 KB)  

    Exemplar-based methods, in which actual image blocks are used to fill in missing content, have achieved state of the art performance in image inpainting. The majority of these adopt a progressive approach, filling in the missing region inwards from the boundary. The final result is highly dependent on fill order, and while significant progress has been made on the choice of this order, the greedy nature of such a process leads to artifacts in some cases. The alternative exemplar-based approach proposed here is defined via joint optimization of a single functional, simultaneously assigning an estimated value to the entire inpainting region. The results are found to be highly competitive with other recent inpainting methods. View full abstract»

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    Publication Year: 2011 , Page(s): 79 - 80
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  • IEEE Signal Processing Letters Information for authors

    Publication Year: 2011 , Page(s): 81 - 82
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  • IEEE copyright form

    Publication Year: 2011 , Page(s): 83 - 84
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Aims & Scope

The IEEE Signal Processing Letters is a monthly, archival publication designed to provide rapid dissemination of original, cutting-edge ideas and timely, significant contributions in signal, image, speech, language and audio processing.

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Meet Our Editors

Editor-in-Chief
Peter Willett
University of Connecticut
Storrs, CT 06269
peter.willett@uconn.edu