http://asp.eurasipjournals.com The latest research articles published by EURASIP Journal on Advances in Signal Processing 2012-05-19T00:00:00Z The pulse response of radar system always suffers from high sidelobe level resulting in resolution degradation. Investigated here is a sidelobe suppression method based on apodization filtering technique for range response of synthetic aperture radar (SAR) and noise SAR system. The core of apodization filtering is finding an appropriate filtering vector in time domain. Compared with original apodization filtering, the proposed method is a modified algorithm with stable realization because it is indeed capable of getting correct filtering vector. This method contains three important steps: constructing coefficient matrix and desired response vector; performing ill-posed analysis; and solving equation to find filtering vector. In these steps, approach of convolution kernel is adopted to construct coefficient matrix; spectral condition is introduced as an indicating function for ill-posed analysis; and total variation method is used to resolve ill-posed equation for getting the filtering vector. Elaborate theoretical derivation is presented to demonstrate the feasibility of this method. In order to test the effects, simulation experiments are executed. And the results show that there is a great suppression of range sidelobes after processed by this method. With increasing filter length, the performance of filtered output is improved but the time cost is increasing correspondingly. Furthermore, the results also indicate that the proposed method is not sensitive to noise disturbance. http://asp.eurasipjournals.com/content/2012/1/112 Xin Wu Yanfei Wang Shu Li Chang Liu EURASIP Journal on Advances in Signal Processing 2012, null:112 2012-05-19T00:00:00Z doi:10.1186/1687-6180-2012-112 /content/figures/1687-6180-2012-112-toc.gif EURASIP Journal on Advances in Signal Processing 1687-6180 ${item.volume} 112 2012-05-19T00:00:00Z PDF This article proposes a new algorithm for finding the angles of arrival of multiple uncorrelated sources impinging on a uniform linear array of sensors. The method is based on sparse signal representation and does not require either the knowledge of the number of the sources or a previous initialization. The proposed technique considers a covariance matrix model based on overcomplete basis representation and tries to fit the unknown signal powers to the sample covariance matrix. Sparsity is enforced by means of a l1-norm penalty. The final problem is reduced to an objective function with a non-negative constraint that can be solved efficiently using the LARS/homotopy algorithm. The method described herein is able to provide high resolution with a low computational burden. It proceeds in an iterative fashion solving at each iteration a small linear system of equations until a stopping condition is fulfilled. The proposed stopping criterion is based on the residual spectrum and arises in a natural way when the LARS/homotopy is applied to the considered objective function. http://asp.eurasipjournals.com/content/2012/1/111 Luis Blanco Montse Najar EURASIP Journal on Advances in Signal Processing 2012, null:111 2012-05-17T00:00:00Z doi:10.1186/1687-6180-2012-111 /content/figures/1687-6180-2012-111-toc.gif EURASIP Journal on Advances in Signal Processing 1687-6180 ${item.volume} 111 2012-05-17T00:00:00Z PDF In this article, a novel image de-noising method is proposed. This method is based on spherical coordinates system. First, spherical transform is re-defined in wavelet domain, and the properties of the spherical transform in wavelet domain are listed. Then, a new adaptive threshold in spherical coordinate system is presented. It has been proved based on Besov space norm theory. After that, a novel curve shrinkage function is proposed to overcome the limitation of the traditional shrinkage functions. The new function can reach and exceed the true value and enhance the edge of the image. Finally, the multi-scale product in wavelet domain is introduced to spherical coordinates system. This article names the multi-scale product in spherical coordinates system as Multi-Scale Norm Product. The experimental results compared the improved algorithm with other methods from the peak signal-to-noise ratio, mean square error and running time. The results indicate that improved algorithm is simple and effective. http://asp.eurasipjournals.com/content/2012/1/110 Degan Zhang Xuejing Kang Jinghui Wang EURASIP Journal on Advances in Signal Processing 2012, null:110 2012-05-16T00:00:00Z doi:10.1186/1687-6180-2012-110 /content/figures/1687-6180-2012-110-toc.gif EURASIP Journal on Advances in Signal Processing 1687-6180 ${item.volume} 110 2012-05-16T00:00:00Z PDF Print media collections of considerable size are held by cultural heritage organizations and will soon be subject to digitization activities. However, technical content quality management in digitization workflows strongly relies on human monitoring. This heavy human intervention is cost intensive and time consuming, which makes automization mandatory. In this article, a new automatic quality assessment and improvement system is proposed. The digitized source image and color reference target are extracted from the raw digitized images by an automatic segmentation process. The target is evaluated by a reference-based algorithm. No-reference quality metrics are applied to the source image. Experimental results are provided to illustrate the performance of the proposed system. We show that it features a good performance in the extraction as well as in the quality assessment step compared to the state-of-the-art. The impact of efficient and dedicated quality assessors on the optimization step is extensively documented. http://asp.eurasipjournals.com/content/2012/1/109 Mohan Liu Iuliu Konya Jan Nandzik Nicolas Flores-Herr Stefan Eickeler Patrick Ndjiki-Nya EURASIP Journal on Advances in Signal Processing 2012, null:109 2012-05-15T00:00:00Z doi:10.1186/1687-6180-2012-109 /content/figures/1687-6180-2012-109-toc.gif EURASIP Journal on Advances in Signal Processing 1687-6180 ${item.volume} 109 2012-05-15T00:00:00Z PDF A novel approach for recognizing human activities with wearable sensors is investigated in this article. The key techniques of this approach include the generalized discriminant analysis (GDA) and the relevance vector machines (RVM). The feature vectors extracted from the measured signal are processed by GDA, with its dimension remarkably reduced from 350 to 12 while fully maintaining the most discriminative information. The reduced feature vectors are then classified by the RVM technique according to an extended multiclass model, which shows good convergence characteristic. Experimental results on the Wearable Action Recognition Dataset demonstrate that our approach achieves an encouraging recognition rate of 99.2%, true positive rate of 99.18% and false positive rate of 0.07%. Although in most cases, the support vector machines model has more than 70 support vectors, the number of relevance vectors related to different activities is always not more than 4, which implies a great simplicity in the classifier structure. Our approach is expected to have potential in real-time applications or solving problems with large-scale datasets, due to its perfect recognition performance, strong ability in feature reduction, and simple classifier structure. http://asp.eurasipjournals.com/content/2012/1/108 Weihua He Yongcai Guo Chao Gao Xinke Li EURASIP Journal on Advances in Signal Processing 2012, null:108 2012-05-10T00:00:00Z doi:10.1186/1687-6180-2012-108 /content/figures/1687-6180-2012-108-toc.gif EURASIP Journal on Advances in Signal Processing 1687-6180 ${item.volume} 108 2012-05-10T00:00:00Z PDF Accurate knowledge of the spatial extents and distributions of an oil spill is very impor-tant for efficient response. This is because most petroleum products spread rapidly on the water surface when released into the ocean, with the majority of the affected area becoming covered by very thin sheets. This article presents a study for examining the feasibility of Landsat ETM+ images in order to detect oil spills pollutions. The Landsat ETM+ images for 1st, 10th, 17th May 2010 were used to study the oil spill in Gulf of Mexico. In this article, an attempt has been made to perform ratio operations to enhance the feature. The study concluded that the bands difference between 660 and 560 nm, division at 660 and 560 and division at 825 and 560 nm, normalized by 480 nm provide the best result. multilayer perceptron neural network classifier is used in order to perform a pixel-based supervised classification. The result indicates the potential of Landsat ETM+ data in oil spill detection. The promising results achieved encourage a further analysis of the potential of the optical oil spill detection approach. http://asp.eurasipjournals.com/content/2012/1/107 Alireza Taravat Fabio Del Frate EURASIP Journal on Advances in Signal Processing 2012, null:107 2012-05-10T00:00:00Z doi:10.1186/1687-6180-2012-107 /content/figures/1687-6180-2012-107-toc.gif EURASIP Journal on Advances in Signal Processing 1687-6180 ${item.volume} 107 2012-05-10T00:00:00Z PDF In radar imaging, resolution is generally dictated by its corresponding system point spread function, the response to a point source as a result of an external excitation. This notion of resolution turns out to be rather questionable, as the interpretation of echoes received from a range of continuous targets according to a linear model allows one to cast the imaging problem as a communication system that maps the target reflectivity function onto measurements, which in turn suggests that by virtue of sampling and equalization, one can achieve unlimited spatial resolution. This article reviews the fundamental problem inherent to pulse compression in a multistatic multi-input-multi-output (MIMO) scenario, from a communications viewpoint, in both focused and unfocused scenarios. We generalize the notion of 1D range compression and replace it by a more general 4D pulse compression. The process of focusing and scanning over a 3D object can be interpreted as a MIMO 4D convolution between a reflectivity tensor and a space-varying system, which naturally induces a 4D MIMO channel convolution model. This implies that several well-established block and linear equalization methods can be easily extended to a 3D scenario with the purpose of achieving exact reconstruction of a given reflectivity volume. That is, assuming that no multiple scattering occurs, resolution is only limited in range by the sampling device in the unfocused case, while unlimited in case of focusing at multiple depths. Exact reconstruction under a zero-forcing or least-squares criterion depends solely on the amount of diversity induced by sampling in both space (via scanning rate) and time (via sampling rate), which further allows for a tradeoff between range and cross-range resolution. For instance, the fastest scanning rate is achieved by steering nonoverlapping beams, in which case portions of the object can be reconstructed independently from each other. http://asp.eurasipjournals.com/content/2012/1/106 Ricardo Merched EURASIP Journal on Advances in Signal Processing 2012, null:106 2012-05-09T00:00:00Z doi:10.1186/1687-6180-2012-106 /content/figures/1687-6180-2012-106-toc.gif EURASIP Journal on Advances in Signal Processing 1687-6180 ${item.volume} 106 2012-05-09T00:00:00Z PDF Sensitivity to carrier frequency offset (CFO) is one of the biggest drawbacks of orthogonal frequency division multiplexing (OFDM) system. A lot of CFO estimation algorithms had been studied for compensation of CFO in OFDM system. However, with the adoption of direct-conversion architecture (DCA), which introduces additional impairments such as dc offset (DCO) and in-phase/quadrature (I/Q) imbalance in OFDM system, the established CFO estimation algorithms suffer from performance degradation. In our previous study, we developed a blind CFO, I/Q imbalance and DCO estimation algorithm for OFDM systems with DCA. In this article, we propose an alternative algorithm with reduced computation complexity and better accuracy. Performance of the proposed algorithm is demonstrated by simulations. http://asp.eurasipjournals.com/content/2012/1/105 Tao Liu Hanzhang Li EURASIP Journal on Advances in Signal Processing 2012, null:105 2012-05-09T00:00:00Z doi:10.1186/1687-6180-2012-105 /content/figures/1687-6180-2012-105-toc.gif EURASIP Journal on Advances in Signal Processing 1687-6180 ${item.volume} 105 2012-05-09T00:00:00Z PDF We study the problem of estimating transfer functions of multivariable (multiple-input multiple-output--MIMO) systems with sparse coefficients. We note that subspace identification methods are powerful and convenient tools in dealing with MIMO systems since they neither require nonlinear optimization nor impose any canonical form on the systems. However, subspace-based methods are inefficient for systems with sparse transfer function coefficients since they work on state space models. We propose a two-step algorithm where the first step identifies the system order using the subspace principle in a state space format, while the second step estimates coefficients of the transfer functions via L1-norm convex optimization. The proposed algorithm retains good features of subspace methods with improved noise-robustness for sparse systems. http://asp.eurasipjournals.com/content/2012/1/104 Wanzhi Qiu Syed Khusro Saleem Efstratios Skafidas EURASIP Journal on Advances in Signal Processing 2012, null:104 2012-05-09T00:00:00Z doi:10.1186/1687-6180-2012-104 /content/figures/1687-6180-2012-104-toc.gif EURASIP Journal on Advances in Signal Processing 1687-6180 ${item.volume} 104 2012-05-09T00:00:00Z PDF Synthetic Aperture Radar (SAR) has proven to be a powerful remote sensing instrument for underground and obscured object detection. However, SAR echoes are often contaminated by Radio Frequency Interferences (RFI) from multiple broadcasting stations. Essentially, RFI suppression problem is one- dimensional stationary time series denoising problem. This paper proposed a novel RFI suppression algorithm based on Singular Spectral Analysis (SSA) from a linear invariant systems perspective. It can be seen that SSA algorithm has an equivalence relation with Finite Impulse Response (FIR) filter banks. Besides, this paper first introduce two approximated methods which can remarkably speed up spectral decomposition--Nystrom method and Column-Sampling approximation--to obtain the coefficients of above SSA-FIR-filter. Simulation results and imaging results of measured data have proved the efficiency and validity of this algorithm. http://asp.eurasipjournals.com/content/2012/1/103 Xiaoyu Wang Weidong Yu Xiangyang Qi Yue Liu EURASIP Journal on Advances in Signal Processing 2012, null:103 2012-05-09T00:00:00Z doi:10.1186/1687-6180-2012-103 /content/figures/1687-6180-2012-103-toc.gif EURASIP Journal on Advances in Signal Processing 1687-6180 ${item.volume} 103 2012-05-09T00:00:00Z PDF