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Signal Processing Letters, IEEE

Issue 1 • Date Jan. 2013

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Displaying Results 1 - 25 of 37
  • Front Cover

    Publication Year: 2013 , Page(s): C1
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    Freely Available from IEEE
  • IEEE Signal Processing Letters publication information

    Publication Year: 2013 , Page(s): C2
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  • Table of Contents

    Publication Year: 2013 , Page(s): 1 - 2
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  • On Perceptually Consistent Image Binarization

    Publication Year: 2013 , Page(s): 3 - 6
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1557 KB) |  | HTML iconHTML  

    Compared with gray images, bi-level images have only two values for each pixel and are more convenient for transmission and storing. Hence, they are very useful in many practical applications such as in image printing and display. Of various image binarization methods, error diffusion is a popular one that can produce perceptually consistent halftone images. However, most of the existing error diffusion techniques have not given rigid theoretical foundation or explicit theoretical derivation, and most of their diffusion domains and diffusion weights are constant, which make them inconvenient to be used and inefficient in some practical applications. In this paper, a new error diffusion scheme for image binarization is derived and established based on the analysis of features of the human visual system (HVS) and the heat transfer theory, where the local image information and the local pixels' value distribution are kept stable or little changed during the binarization process. As a result, the overall visual quality of binarized images can be kept perceptually similar to the original ones. Experiments are conducted and convincing results are acquired. View full abstract»

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  • A Steerable, Multiscale Singularity Index

    Publication Year: 2013 , Page(s): 7 - 10
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2058 KB) |  | HTML iconHTML  

    We propose a new steerable, multiscale ratio index for detecting impulse singularities in signals of arbitrary dimensionality. For example, it responds strongly to curvilinear masses (ridges) in images, but minimally to step discontinuities. The ratio index employs directional derivatives of gaussians, making it naturally steerable and scalable. Experiments on real images demonstrate the efficacy of the index for detecting multiscale curvilinear structures. A software version of the index can be downloaded from: http://live.ece.utexas.edu/research/SingularityIndex/SingularityIndex.zip. View full abstract»

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  • Joint Voltage and Phase Unbalance Detector for Three Phase Power Systems

    Publication Year: 2013 , Page(s): 11 - 14
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1113 KB) |  | HTML iconHTML  

    This letter develops a fast detection algorithm for voltage and phase unbalance in three phase power systems. It is suitable for real time applications since the required observation length is one cycle. It is shown to successfully detect small unbalance conditions at low SNRs. Its detection performance is shown to outperform traditional detectors that rely on changes in only a subset of positive, negative and zero sequence voltages. Unbalance detection is formulated as a hypothesis test under a framework of detection theory and solved by applying a generalized likelihood ratio test (GLRT). We first obtain an approximate maximum likelihood estimate (MLE) of the system frequency and then use it to substitute the true unknown frequency in the GLRT. A closed form expression is provided to detect unbalance conditions. Theoretical derivations are supported by simulations. View full abstract»

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  • Shifted-Delta MLP Features for Spoken Language Recognition

    Publication Year: 2013 , Page(s): 15 - 18
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (583 KB) |  | HTML iconHTML  

    This letter presents our study of applying phoneme posterior features for spoken language recognition (SLR). In our work, phoneme posterior features are estimated from a multilayer perceptron (MLP) based phoneme recognizer, and are further processed through transformations including taking logarithm, PCA transformation, and appending shifted delta coefficients. The resulting shifted-delta MLP (SDMLP) features show similar distribution as conventional shifted-delta cepstral (SDC) features, and are more robust compared to the SDC features. Experiments on the NIST LRE2005 dataset show that the SDMLP features fit well with the state-of-the-art GMM-based SLR systems, and SDMLP features outperform SDC features significantly. View full abstract»

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  • Face Hallucination via Similarity Constraints

    Publication Year: 2013 , Page(s): 19 - 22
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1199 KB) |  | HTML iconHTML  

    In this letter, we present a new face hallucination method based on similarity constraints to produce a high-resolution (HR) face image from an input low-resolution (LR) face image. This method is modeled as a local linear filtering process by incorporating four constraint functions at patch level. The first two constraints focus on checking if the training images are similar to the input face image. The third is defined in the HR face image, which is to impose the smoothness constraint between neighboring hallucinated patches. The final constraint computes the spatial distance to reduce the effect of patches that are far from the hallucinating patch. Experimental evaluation on a number of face images demonstrates the good performance of the proposed method on the face hallucination task. View full abstract»

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  • On the Step-Size Bounds of Frequency-Domain Block LMS Adaptive Filters

    Publication Year: 2013 , Page(s): 23 - 26
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (871 KB) |  | HTML iconHTML  

    Least-mean-square (LMS) and block LMS (BLMS) adaptive filters are generally believed to have similar step-size bounds for convergence. Similarly, convergence analyses of frequency-domain block LMS (FBLMS) adaptive filters have suggested that they have very restrictive convergence bounds. In this letter, we revisit Feuer's work and reveal a much larger convergence bound for BLMS adaptive filters. We then analyze the convergence properties of the FBLMS adaptive filter. The new step-size bound for the FBLMS adaptive filter, regardless of whether the input is white or colored, is not that restrictive as generally assumed for the block algorithms in the literature. Extensive simulation results are included to support the analyses. View full abstract»

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  • Max-Min Fairness Linear Transceiver Design Problem for a Multi-User SIMO Interference Channel is Polynomial Time Solvable

    Publication Year: 2013 , Page(s): 27 - 30
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (973 KB) |  | HTML iconHTML  

    Consider the linear transceiver design problem for a multi-user single-input multi-output (SIMO) interference channel. Assuming perfect channel knowledge, we formulate this problem as one of maximizing the minimum signal to interference plus noise ratio (SINR) among all the users, subject to individual power constraints at each transmitter. We prove in this letter that the max-min fairness linear transceiver design problem for the SIMO interference channel can be solved to global optimality in polynomial time. We further propose a low-complexity inexact cyclic coordinate ascent algorithm (ICCAA) to solve this problem. Numerical simulations show the proposed algorithm can efficiently find the global optimal solution of the considered problem. View full abstract»

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  • Performance Optimization of Digital Spectrum Analyzer With Gaussian Input Signal

    Publication Year: 2013 , Page(s): 31 - 34
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (709 KB) |  | HTML iconHTML  

    Analog to digital converters (ADC) and cascade integrator-comb (CIC) filters are the basic modules in a digital intermediate frequency (IF) spectrum analyzer. The optimal output signal-to-noise ratio (SNR) of the digital IF spectrum analyzer with the Gaussian input signal is considered in this letter. The idea is to strike a trade-off between the saturation error and granular error when quantizing the Gaussian input signal. This letter firstly derives a relationship among the maximum allowed input signal amplitude, input signal power, ADC quantization bits and optimal quantization SNR. Besides, an optimal clipping strategy for the CIC decimation filter with variable decimation rates is proposed. Both numerical and simulation results are presented to demonstrate that the proposed clipping method is able to achieve significant SNR gain compared with the traditional rounding or truncation method. View full abstract»

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  • Cooperative Secure Beamforming for AF Relay Networks With Multiple Eavesdroppers

    Publication Year: 2013 , Page(s): 35 - 38
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1138 KB) |  | HTML iconHTML  

    This letter studies cooperative secure beamforming for amplify-and-forward (AF) relay networks in the presence of multiple eavesdroppers. Under both total and individual relay power constraints, we propose two schemes, namely secrecy rate maximization (SRM) beamforming and null-space beamforming. In the first scheme, our design problem is based on SRM. Using a suboptimal, but convex, technique-semidefinite relaxation (SDR), we show that this problem can be handled by performing a one-dimensional search which involves solving a sequence of semidefinite programs (SDPs). To reduce the complexity, in the second scheme, we instead maximize the information rate at the destination while completely eliminating the information leakage to all eavesdroppers. We prove that this problem can be exactly solved by SDR with one SDP only. Simulation results demonstrate the performance gains of the two proposed designs. View full abstract»

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  • Joint Cooperative Beamforming and Jamming to Secure AF Relay Systems With Individual Power Constraint and No Eavesdropper's CSI

    Publication Year: 2013 , Page(s): 39 - 42
    Cited by:  Papers (19)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1246 KB) |  | HTML iconHTML  

    Cooperative beamforming and jamming are two efficient schemes to improve the physical-layer security of a wireless relay system in the presence of passive eavesdroppers. However, in most works these two techniques are adopted separately. In this letter, we propose a joint cooperative beamforming and jamming scheme to enhance the security of a cooperative relay network, where a part of intermediate nodes adopt distributed beamforming while others jam the eavesdropper, simultaneously. Since the instantaneous channel state information (CSI) of the eavesdropper may not be known, we propose a cooperative artificial noise transmission based secrecy strategy, subjected to the individual power constraint of each node. The beamformer weights and power allocation can be obtained by solving a second-order convex cone programming (SOCP) together with a linear programming problem. Simulations show the joint scheme greatly improves the security. View full abstract»

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  • Power Allocation for Statistical QoS Provisioning in Opportunistic Multi-Relay DF Cognitive Networks

    Publication Year: 2013 , Page(s): 43 - 46
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1307 KB) |  | HTML iconHTML  

    In this letter, we propose a power allocation scheme for statistical quality-of-service (QoS) provisioning in multi-relay decode-and-forward (DF) cognitive networks (CN). By considering the direct link between the source and destination, the CN first chooses the transmission mode (direct transmission or relay transmission) based on the channel state information. Then, according to the determined transmission mode, efficient power allocation will be performed under the given QoS requirement, the average transmit and interference power constraints as well as the peak interference constraint. Our proposed power allocation scheme indicates that, in order to achieve the maximum throughput, at most two relays can be involved for the transmission. Simulation results show that our proposed scheme outperforms the max-min criterion and equal power allocation policy. View full abstract»

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  • Receiver-Driven Adaptive Enhancement Layer Switching Algorithm for Scalable Video Transmission Over Link-adaptive Networks

    Publication Year: 2013 , Page(s): 47 - 50
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (430 KB) |  | HTML iconHTML  

    A receiver-driven adaptive layer switching algorithm is proposed for adapting the video bitrate to match the achievable network throughput. It relies on a QoS-constrained equivalent bandwidth estimator employed at the receiver, which is used for triggering the adjustment of video layers at the video source. Simulations are conducted to illustrate its efficiency by showing that it is capable of accommodating different channel qualities without their prior knowledge. View full abstract»

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  • Joint Clock Synchronization and Ranging: Asymmetrical Time-Stamping and Passive Listening

    Publication Year: 2013 , Page(s): 51 - 54
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1057 KB) |  | HTML iconHTML  

    A fully asynchronous network with one sensor and M anchors (nodes with known locations) is considered in this letter. We propose a novel asymmetrical time-stamping and passive listening (ATPL) protocol for joint clock synchronization and ranging. The ATPL protocol exploits broadcast to not only reduce the number of active transmissions between the nodes, but also to obtain more information. This is used in a simple estimator based on least-squares (LS) to jointly estimate all the unknown clock-skews, clock-offsets, and pairwise distances of the sensor to each anchor. The Cramér-Rao lower bound (CRLB) is derived for the considered problem. The proposed estimator is shown to be asymptotically efficient, meets the CRLB, and also performs better than the available clock synchronization algorithms. View full abstract»

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  • Bit Error-Rate Minimizing Detector for Amplify-and-Forward Relaying Systems Using Generalized Gaussian Kernel

    Publication Year: 2013 , Page(s): 55 - 58
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (856 KB) |  | HTML iconHTML  

    In this letter, a new detector is proposed for amplify-and-forward (AF) relaying system when communicating with the assistance of L relays. The major goal of this detector is to improve the bit error rate (BER) performance of the receiver. The probability density function is estimated with the help of kernel density technique. A generalized Gaussian kernel is proposed. This new kernel provides more flexibility and encompasses Gaussian and uniform kernels as special cases. The optimal window width of the kernel is calculated. Simulations results show that a gain of more than 1 dB can be achieved in terms of BER performance as compared to the minimum mean square error (MMSE) receiver when communicating over Rayleigh fading channels. View full abstract»

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  • Local Polar DCT Features for Image Description

    Publication Year: 2013 , Page(s): 59 - 62
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (654 KB) |  | HTML iconHTML  

    We present a novel feature descriptor, Local Polar DCT Features (LPDF), which is robust to a variety of image transformations. Specifically, the local patch is quantized in the designed polar geometric structure and the 2-D DCT features are then extracted and rearranged. A subset of the resulting DCT coefficients is selected as our compact LPDF descriptor. We perform a comprehensive performance evaluation with state-of-the-art methods, i.e., SIFT, DAISY, LIOP, and GLOH on the standard Oxford dataset and two additional test image pairs. Experimental results demonstrate the superiority of proposed descriptor under various image transformations, even with very low dimensions. View full abstract»

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  • Probabilistic Subspace Clustering Via Sparse Representations

    Publication Year: 2013 , Page(s): 63 - 66
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1032 KB) |  | HTML iconHTML  

    We present a probabilistic subspace clustering approach that is capable of rapidly clustering very large signal collections. Each signal is represented by a sparse combination of basis elements (atoms), which form the columns of a dictionary matrix. The set of sparse representations is utilized to derive the co-occurrences matrix of atoms and signals, which is modeled as emerging from a mixture model. The components of the mixture model are obtained via a non-negative matrix factorization (NNMF) of the co-occurrences matrix, and the subspace of each signal is estimated according to a maximum-likelihood (ML) criterion. Performance evaluation demonstrate comparable clustering accuracies to state-of-the-art at a fraction of the computational load. View full abstract»

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  • Reference-Based Scheme Combined With K-SVD for Scene Image Categorization

    Publication Year: 2013 , Page(s): 67 - 70
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (794 KB) |  | HTML iconHTML  

    A reference-based algorithm for scene image categorization is presented in this letter. In addition to using a reference-set for images representation, we also associate the reference-set with training data in sparse codes during the dictionary learning process. The reference-set is combined with the reconstruction error to form a unified objective function. The optimal solution is efficiently obtained using the K-SVD algorithm. After dictionaries are constructed, Locality-constrained Linear Coding (LLC) features of images are extracted. Then, we represent each image feature vector using the similarities between the image and the reference-set, leading to a significant reduction of the dimensionality in the feature space. Experimental results demonstrate that our method achieves outstanding performance. View full abstract»

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  • Blind Separation of Complex Sources Using Generalized Generating Function

    Publication Year: 2013 , Page(s): 71 - 74
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (923 KB) |  | HTML iconHTML  

    We propose a new blind separation approach based on the Generalized Generating Function (GGF) of observations for complex sources by generalizing the definition of generating function. A new core equation is obtained and an approximate joint diagonalization scheme is used to estimate the mixing matrix by diagonalizing the Hessian matrix of the second GGF of the observations. Simulation results show that the GGF approach has superior performance to the existing classical algorithms when the SNR of observations is low and the data block is short. View full abstract»

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  • Asymptotic Analysis of Switched Uniform Polar Quantization for Memoryless Gaussian Source

    Publication Year: 2013 , Page(s): 75 - 78
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1503 KB) |  | HTML iconHTML  

    This letter performs an asymptotic analysis of the switched uniform polar quantizer (SUPQ) composed of k asymptotically optimal unrestricted uniform polar quantizers designed for the memoryless Gaussian source. The closed-form formulas are derived for signal to quantization noise ratio (SQNR) and the number of phase levels of the quantizers constituting the SUPQ. It is studied how SQNR depends on the variance mismatch and the number of quantizers k. It is shown that with a log-uniform distribution of the variances for which the quantizers constituting the SUPQ are designed one can reduce the variance range of average-taking of SQNR. View full abstract»

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  • Improving Dictionary Learning: Multiple Dictionary Updates and Coefficient Reuse

    Publication Year: 2013 , Page(s): 79 - 82
    Cited by:  Papers (7)
    Multimedia
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (612 KB)  

    In this letter, we propose two improvements of the MOD and K-SVD dictionary learning algorithms, by modifying the two main parts of these algorithms-the dictionary update and the sparse coding stages. Our first contribution is a different dictionary-update stage that aims at finding both the dictionary and the representations while keeping the supports intact. The second contribution suggests to leverage the known representations from the previous sparse-coding in the quest for the updated representations. We demonstrate these two ideas in practice and show how they lead to faster training and better quality outcome. View full abstract»

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  • Collaborative Blind Source Separation Using Location Informed Spatial Microphones

    Publication Year: 2013 , Page(s): 83 - 86
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (782 KB) |  | HTML iconHTML  

    This letter presents a new Collaborative Blind Source Separation (CBSS) technique that uses a pair of location informed coincident microphone arrays to jointly separate simultaneous speech sources based on time-frequency source localization estimates from each microphone recording. While existing BSS approaches are based on localization estimates of sparse time-frequency components, the proposed approach can also recover non-sparse (overlapping) time-frequency components. The proposed method has been evaluated using up to three simultaneous speech sources under both anechoic and reverberant conditions. Results from objective and subjective measures of the perceptual quality of the separated speech show that the proposed approach significantly outperforms existing BSS approaches. View full abstract»

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  • Nonlinear Depth Map Resampling for Depth-Enhanced 3-D Video Coding

    Publication Year: 2013 , Page(s): 87 - 90
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (490 KB) |  | HTML iconHTML  

    Depth-enhanced 3-D video coding includes coding of texture views and associated depth maps. It has been observed that coding of depth map at reduced resolution provides better rate-distortion performance on synthesized views comparing to utilization of full resolution (FR) depth maps in many coding scenarios based on the Advanced Video Coding (H.264/AVC) standard. Conventional techniques for down and upsampling do not take typical characteristics of depth maps, such as distinct edges and smooth regions within depth objects, into account. Hence, more efficient down and upsampling tools, capable of preserving edges better, are needed. In this letter, novel non-linear methods to down and upsample depth maps are presented. Bitrate comparison of synthesized views, including texture and depth map bitstreams, is presented against a conventional linear resampling algorithm. Objective results show an average bitrate reduction of 5.29% and 3.31% for the proposed down and upsampling methods with ratio ½, respectively, comparing to the anchor method. Moreover, a joint utilization of the proposed down and upsampling brings up to 20% and on average 7.35% bitrate reduction. View full abstract»

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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