http://www.hindawi.com The latest articles from Hindawi Publishing Corporation © 2013 , Hindawi Publishing Corporation . All rights reserved. Sun, 19 May 2013 14:25:21 +0000 http://www.hindawi.com/isrn/sp/2013/928971/ We develop a multiexposure image fusion method based on texture features, which exploits the edge preserving and intraregion smoothing property of nonlinear diffusion filters based on partial differential equations (PDE). With the captured multiexposure image series, we first decompose images into base layers and detail layers to extract sharp details and fine details, respectively. The magnitude of the gradient of the image intensity is utilized to encourage smoothness at homogeneous regions in preference to inhomogeneous regions. Then, we have considered texture features of the base layer to generate a mask (i.e., decision mask) that guides the fusion of base layers in multiresolution fashion. Finally, well-exposed fused image is obtained that combines fused base layer and the detail layers at each scale across all the input exposures. Proposed algorithm skipping complex High Dynamic Range Image (HDRI) generation and tone mapping steps to produce detail preserving image for display on standard dynamic range display devices. Moreover, our technique is effective for blending flash/no-flash image pair and multifocus images, that is, images focused on different targets. Harbinder Singh, Vinay Kumar, and Sunil Bhooshan Copyright © 2013 Harbinder Singh et al. All rights reserved. Mon, 13 May 2013 14:23:27 +0000 http://www.hindawi.com/isrn/sp/2013/894542/ An adaptive selection combining (SC) scheme is proposed for time varying mobile communication channel in Class-A impulsive noise. The receiver adaptively selects a diversity branch out of the available branches and discards the others. This is performed by computing the maximum likelihood (ML) metric of each diversity branch and selects the branch with the maximum metric. The proposed adaptive SC scheme dynamically adjusts the threshold value according to the time variations of the channel. Equalization and data detection are performed after combining using maximum likelihood sequence estimation implemented by Viterbi algorithm (MLSE-VA). The minimum survivor technique is employed to reduce the complexity of the receiver. Ahmed El-Sayed El-Mahdy Copyright © 2013 Ahmed El-Sayed El-Mahdy. All rights reserved. Wed, 08 May 2013 15:26:11 +0000 http://www.hindawi.com/isrn/sp/2013/735857/ This paper addresses the problems encountered during digitization and preservation of inscriptions such as perspective distortion and minimal distinction between foreground and background. In general inscriptions possess neither standard size and shape nor colour difference between the foreground and background. Hence the existing methods like variance based extraction and Fast ICA based analysis fail to extract text from these inscription images. Natural gradient flexible ICA (NGFICA) is a suitable method for separating signals from a mixture of highly correlated signals, as it minimizes the dependency among the signals by considering the slope of the signal at each point. We propose an NGFICA based enhancement of inscription images. The proposed method improves word and character recognition accuracies of the OCR system by 65.3% (from 10.1% to 75.4%) and 54.3% (from 32.4% to 86.7%), respectively. Indu Sreedevi, Rishi Pandey, N. Jayanthi, Geetanjali Bhola, and Santanu Chaudhury Copyright © 2013 Indu Sreedevi et al. All rights reserved. Thu, 28 Mar 2013 08:27:55 +0000 http://www.hindawi.com/isrn/sp/2013/859590/ Estimating the direction of arrival (DOA) of source signals is an important research interest in application areas including radar, sonar, and wireless communications. In this paper, the problem of DOA estimation is addressed on concentric circular antenna arrays (CCA) in detail as an alternative to the well-known geometries of the uniform linear array (ULA) and uniform circular array (UCA). We define the steering matrix of the CCA geometry and investigate the performance analysis of the array in the DOA-estimation problem by simulations that are realized through varying the parameters of signal-to-noise ratio, number of sensors, and resolution angle of sensor arrays by using the MUSIC (Multiple Signal Classification) algorithm. The results present that CCA geometries provide higher angle resolutions compared to UCA geometries and require less physical area for the same number of sensor elements. However, as a cost-increasing effect, higher computational power is needed to estimate the DOA of source signals in CCAs compared to ULAs. Serdar Ozgur Ata and Cevdet Isik Copyright © 2013 Serdar Ozgur Ata and Cevdet Isik. All rights reserved. Thu, 07 Mar 2013 15:14:47 +0000 http://www.hindawi.com/isrn/sp/2013/605035/ This paper models and solves the mathematical problem of interpolating characteristic points of signals by a partial differential Equation-(PDE-) based approach. The existence and uniqueness results are established in an appropriate space whose regularity is similar to cubic spline one. We show how this space is suitable for the empirical mode decomposition (EMD) sifting process. Numerical schemes and computing applications are also presented for signal envelopes calculation. The test results show the usefulness of the new PDE interpolator in some pathological cases like input class functions that are not so regular as in the cubic splines case. Some image filtering tests strengthen the demonstration of PDE interpolator performance. Oumar Niang, Abdoulaye Thioune, Éric Deléchelle, Mary Teuw Niane, and Jacques Lemoine Copyright © 2013 Oumar Niang et al. All rights reserved. Wed, 20 Feb 2013 09:56:31 +0000 http://www.hindawi.com/isrn/sp/2013/374064/ Current measures of causality and temporal precedence have limited frequency and time resolution and therefore may not be viable in the detection of short periods of causality in specific frequencies. In addition, the presence of nonstationarities hinders the causality estimation of current techniques as they are based on Fourier transforms or autoregressive model estimation. In this work we present a combination of techniques to measure causality and temporal precedence between stationary and nonstationary time series, that is sensitive to frequency-specific short episodes of causality. This methodology provides a highly informative time-frequency representation of causality with existing causality measures. This is done by decomposing each time series into intrinsic oscillatory modes with an empirical mode decomposition algorithm and, subsequently, calculating their complex Hilbert spectrum. At each time point the cross-spectrum is calculated between time series and used to measure coherency and compute the transfer function and error covariance matrices using the Wilson-Burg method for spectral factorization. The imaginary part of coherency can then be computed as well as several Granger causality measures in the previous matrices. This work covers the most important theoretical background of these techniques and tries to prove the usefulness of this new approach while pointing out some of its qualities and drawbacks. João Rodrigues and Alexandre Andrade Copyright © 2013 João Rodrigues and Alexandre Andrade. All rights reserved. Wed, 13 Feb 2013 15:03:02 +0000 http://www.hindawi.com/isrn/sp/2013/417492/ The subspace segmentation problem is fundamental in many applications. The goal is to cluster data drawn from an unknown union of subspaces. In this paper we state the problem and describe its connection to other areas of mathematics and engineering. We then review the mathematical and algorithmic methods created to solve this problem and some of its particular cases. We also describe the problem of motion tracking in videos and its connection to the subspace segmentation problem and compare the various techniques for solving it. Akram Aldroubi Copyright © 2013 Akram Aldroubi. All rights reserved. Wed, 13 Feb 2013 14:03:47 +0000 http://www.hindawi.com/isrn/sp/2013/218651/ A blind source separation method is described to extract sources from data mixtures where the underlying sources are sparse and correlated. The approach used is to detect and analyze segments of time where one source exists on its own. The method does not assume independence of sources and probability density functions are not assumed for any of the sources. A comparison is made between the proposed method and the Fast-ICA and Clusterwise PCA methods. It is shown that the proposed method works best for cases where the underlying sources are strongly correlated because Fast-ICA assumes zero correlation between sources and Clusterwise PCA can be sensitive to overlap between sources. However, for cases of sources that are sparse and weakly correlated with each other, there is a tendency for Fast-ICA and Clusterwise PCA to have better performances than the proposed method, the reason being that these methods appear to be more robust to changes in input parameters to the algorithms. In addition, because of the deflationary nature of the proposed method, there is a tendency for estimates to be more affected by noise than Fast-ICA when the number of sources increases. The paper concludes with a discussion concerning potential applications for the proposed method. M. S. Woolfson, C. Bigan, J. A. Crowe, and B. R. Hayes-Gill Copyright © 2013 M. S. Woolfson et al. All rights reserved. Wed, 06 Feb 2013 16:17:13 +0000 http://www.hindawi.com/isrn/sp/2013/905685/ Image quality assessment (IQA) has been a topic of intense research over the last several decades. With each year comes an increasing number of new IQA algorithms, extensions of existing IQA algorithms, and applications of IQA to other disciplines. In this article, I first provide an up-to-date review of research in IQA, and then I highlight several open challenges in this field. The first half of this article provides discuss key properties of visual perception, image quality databases, existing full-reference, no-reference, and reduced-reference IQA algorithms. Yet, despite the remarkable progress that has been made in IQA, many fundamental challenges remain largely unsolved. The second half of this article highlights some of these challenges. I specifically discuss challenges related to lack of complete perceptual models for: natural images, compound and suprathreshold distortions, and multiple distortions, and the interactive effects of these distortions on the images. I also discuss challenges related to IQA of images containing nontraditional, and I discuss challenges related to the computational efficiency. The goal of this article is not only to help practitioners and researchers keep abreast of the recent advances in IQA, but to also raise awareness of the key limitations of current IQA knowledge. Damon M. Chandler Copyright © 2013 Damon M. Chandler. All rights reserved. Wed, 23 Jan 2013 10:52:53 +0000 http://www.hindawi.com/isrn/sp/2013/356291/ We study a new MART-AP algorithm of few-views discrete tomography. Its efficiency for high-frequency structure reproduction is investigated in a numerical experiment where we reconstruct a 2D model for the estimation of the spatial resolution limit. We estimate the modulation transfer function of the reconstruction algorithm and compare it with the modulation transfer function of projection distortions. Our results show that MART-AP weakly influences the contrast of spatial structures being reproduced and can be used for high-resolution reconstruction when only a few projections are registered. Alexander B. Konovalov and Vitaly V. Vlasov Copyright © 2013 Alexander B. Konovalov and Vitaly V. Vlasov. All rights reserved. Thu, 10 Jan 2013 09:39:27 +0000 http://www.hindawi.com/isrn/sp/2013/496701/ The aim of this survey is to provide a comprehensive overview of the state of the art in the area of image forensics. These techniques have been designed to identify the source of a digital image or to determine whether the content is authentic or modified, without the knowledge of any prior information about the image under analysis (and thus are defined as passive). All these tools work by detecting the presence, the absence, or the incongruence of some traces intrinsically tied to the digital image by the acquisition device and by any other operation after its creation. The paper has been organized by classifying the tools according to the position in the history of the digital image in which the relative footprint is left: acquisition-based methods, coding-based methods, and editing-based schemes. Alessandro Piva Copyright © 2013 Alessandro Piva. All rights reserved. Wed, 26 Dec 2012 10:45:32 +0000 http://www.hindawi.com/isrn/sp/2012/306305/ A new log-power domain feature enhancement algorithm named NLPS is developed. It consists of two parts, direct solution of nonlinear system model and log-power subtraction. In contrast to other methods, the proposed algorithm does not need prior speech/noise statistical model. Instead, it works by direct solution of the nonlinear function derived from the speech recognition system. Separate steps are utilized to refine the accuracy of estimated cepstrum by log-power subtraction, which is the second part of the proposed algorithm. The proposed algorithm manages to solve the speech probability distribution function (PDF) discontinuity problem caused by traditional spectral subtraction series algorithms. The effectiveness of the proposed filter is extensively compared using the standard database, AURORA2. The results show that significant improvement can be achieved by incorporating the proposed algorithm. The proposed algorithm reaches a recognition rate of over 86% for noisy speech (average from SNR 0 dB to 20 dB), which means a 48% error reduction over the baseline Mel-frequency Cepstral Coefficient (MFCC) system. Peng Dai, Ing Yann Soon, and Rui Tao Copyright © 2012 Peng Dai et al. All rights reserved. Tue, 18 Dec 2012 11:12:02 +0000 http://www.hindawi.com/isrn/sp/2012/781940/ We have addressed a novel watermarking algorithm to support the capacity demanded by the multimodal biometric templates. Proposed technique embeds watermark in low frequency AC coefficients of selected 8 × 8 DCT blocks. Selection of blocks accomplishes perceptual transparency by exploiting the masking effects of human visual system (HVS). Embedding is done by modulating the coefficient magnitude as a function of its estimated value. Neighborhood estimation is used for the weighted DC coefficients from eight neighboring DCT blocks. The weights of the DC coefficients are calculated from local image intrinsic property. For our experimentation we have used iris and finger prints as the two templates which are watermarked into standard test images. The robustness of the proposed algorithm is compared with the few state-of-the-art literature when watermarked image is subjected to common channel attacks. Mita Paunwala and S. Patnaik Copyright © 2012 Mita Paunwala and S. Patnaik. All rights reserved. Mon, 17 Dec 2012 13:59:37 +0000 http://www.hindawi.com/isrn/sp/2012/179087/ Tracking of arterial walls in ultrasound image sequences is useful for studying the dynamics of arteries. Manual delineation is prohibitively labour intensive and existing methods of computerized segmentation are limited in terms of applicability and availability. This paper presents a probabilistic approach to the computerized tracking of arterial walls that is effective and easy to implement. In the probabilistic approach, given a point B with a probability of being in an arterial lumen of interest, the probability that a neighbouring point A is also a part of the same lumen is proportional to with a Gaussian fall in probability with increasing grayscale contrast between the two points. Efficacy of the probabilistic algorithm was evaluated by testing it on ultrasound images and image sequences of the carotid arteries and the abdominal aorta and various laboratory, ultrasound test objects. The results showed that the probabilistic algorithm produced robust and effective lumen segmentation in the majority of cases encountered. Comparison with a conventional region growing technique based on intensity thresholding with a running, regional intensity average identified the main benefits of the probabilistic approach as increased immunity to speckle noise within the arterial lumen and a reduced susceptibility to region overflowing at boundary imperfections. Baris Kanber and Kumar Vids Ramnarine Copyright © 2012 Baris Kanber and Kumar Vids Ramnarine. All rights reserved. Thu, 13 Dec 2012 16:03:28 +0000 http://www.hindawi.com/isrn/sp/2012/457152/ We propose a new method called spectral intrinsic decomposition (SID) for the representation of nonlinear signals. This approach is based on the spectral decomposition of partial differential equation- (PDE-) based operators which interpolate the characteristic points of a signal. The SID’s components which are the eigenvectors of these PDE interpolation operators underlie the new signal decomposition-reconstruction method. The usefulness and the efficiency of this method is illustrated, in signal reconstruction or denoising aim, in some examples using artificial and pathological signals. Oumar Niang, Abdoulaye Thioune, Éric Deléchelle, and Jacques Lemoine Copyright © 2012 Oumar Niang et al. All rights reserved. Tue, 16 Oct 2012 16:45:18 +0000 http://www.hindawi.com/isrn/sp/2012/121628/ The established statistical analysis, already used to treat overhead transmission power grid networks, is now implemented to examine the factors influencing modal transmission characteristics and modal statistical performance metrics of overhead and underground low-voltage/broadband over power lines (LV/BPL) and medium-voltage/broadband over power lines (MV/BPL) channels associated with power distribution in smart grid (SG) networks. The novelty of this paper is threefold. First, a refined multidimensional chain scattering matrix (TM2) method suitable for overhead and underground LV/BPL and MV/BPL modal channels is evaluated against other relative theoretical and experimental proven models. Second, applying TM2 method, the end-to-end modal channel attenuation of various LV/BPL and MV/BPL multiconductor transmission line (MTL) configurations is determined. The LV/BPL and MV/BPL transmission channels are investigated with regard to their spectral behavior and their end-to-end modal channel attenuation. It is found that the above features depend drastically on the frequency, the type of power grid, the mode considered, the MTL configuration, the physical properties of the cables used, the end-to-end distance, and the number, the electrical length, and the terminations of the branches encountered along the end-to-end BPL signal propagation. Third, the statistical properties of various overhead and underground LV/BPL and MV/BPL modal channels are investigated revealing the correlation between end-to-end modal channel attenuation and modal root-mean-square delay spread (RMS-DS). Already verified in the case of overhead high-voltage (HV) BPL systems, this fundamental property of several wireline systems is also modally validated against relevant sets of field measurements, numerical results, and recently proposed statistical channel models for various overhead and underground LV/BPL and MV/BPL channels. Based on this common inherent attribute of either transmission or distribution BPL networks, new unified regression trend line is proposed giving a further boost towards BPL system intraoperability. A consequence of this paper is that it aids in gaining a better understanding of the range and coverage that BPL solutions can achieve; a preliminary step toward the system symbiosis between BPL systems and other broadband technologies in an SG environment. Athanasios G. Lazaropoulos Copyright © 2012 Athanasios G. Lazaropoulos. All rights reserved. Tue, 16 Oct 2012 09:42:19 +0000 http://www.hindawi.com/isrn/sp/2012/870276/ In the present paper, we discuss a method to design a linear phase 1-dimensional Infinite Impulse Response (IIR) filter using orthogonal polynomials. The filter is designed using a set of object functions. These object functions are realized using a set of orthogonal polynomials. The method includes placement of zeros and poles in such a way that the amplitude characteristics are not changed while we change the phase characteristics of the resulting IIR filter. Vinay Kumar and Sunil Bhooshan Copyright © 2012 Vinay Kumar and Sunil Bhooshan. All rights reserved. Sun, 14 Oct 2012 14:50:44 +0000 http://www.hindawi.com/isrn/sp/2012/614653/ The -Distribution is an important clutter model for high-resolution radar sea clutter returns obtained at X-band. The Neyman-Pearson optimal multilook detector has been derived recently, as well as the generalised likelihood ratio test suboptimal detector. Both these detectors are dependent on the modified Bessel-function of the second kind. This paper suggests a suitable suboptimal approach, using a well-known Bessel identity, eliminating the Bessel function dependence. This produces a computationally simpler detection scheme, whose performance is analysed using clutter parameters based upon real X-band radar returns. G. V. Weinberg Copyright © 2012 G. V. Weinberg. All rights reserved. Tue, 14 Aug 2012 08:51:35 +0000 http://www.hindawi.com/isrn/sp/2012/740761/ We describe and analyze a simple and effective two-step online boosting algorithm that allows us to utilize highly effective gradient descent-based methods developed for online SVM training without the need to fine-tune the kernel parameters, and we show its efficiency by several experiments. Our method is similar to AdaBoost in that it trains additional classifiers according to the weights provided by previously trained classifiers, but unlike AdaBoost, we utilize hinge-loss rather than exponential loss and modify algorithm for the online setting, allowing for varying number of classifiers. We show that our theoretical convergence bounds are similar to those of earlier algorithms, while allowing for greater flexibility. Our approach may also easily incorporate additional nonlinearity in form of Mercer kernels, although our experiments show that this is not necessary for most situations. The pre-training of the additional classifiers in our algorithms allows for greater accuracy while reducing the times associated with usual kernel-based approaches. We compare our algorithm to other online training algorithms, and we show, that for most cases with unknown kernel parameters, our algorithm outperforms other algorithms both in runtime and convergence speed. Vsevolod Yugov and Itsuo Kumazawa Copyright © 2012 Vsevolod Yugov and Itsuo Kumazawa. All rights reserved. Wed, 01 Aug 2012 07:27:39 +0000 http://www.hindawi.com/isrn/sp/2012/628706/ We present a method for coding speech signals for the simulation of a cochlear implant. The method is based on a wavelet packet decomposition strategy. We used wavelet packet db4 for 7 levels, generated a series of channels with bandwidths exactly the same as nucleus device, and applied an input stimulus to each channel. The processed signal was then reconstructed and compared to the original signal, which preserved the contents to a high percentage. Finally, performance of the wavelet packet decomposition in terms of computational complexity was compared to other commonly used strategies in cochlear implants. The results showed the power of this method in processing of the input signal for implant users with less complexity than other methods, while maintaining the contents of the input signal to a very good extent. M. Mehrzad, M. D. Abolhassani, A. H. Jafari, J. Alirezaie, and M. Sangargir Copyright © 2012 M. Mehrzad et al. All rights reserved. Thu, 26 Jul 2012 13:20:24 +0000 http://www.hindawi.com/isrn/sp/2012/712032/ This paper presents the effectiveness of bioelectrical signals such as the electrocardiogram (ECG) and the electroencephalogram (EEG) for biometric applications. Studies show that the impulses of cardiac rhythm and electrical activity of the brain recorded in ECG and EEG, respectively; have unique features among individuals, therefore they can be suggested to be used as biometrics for identity verification. The favourable characteristics to use the ECG or EEG signals as biometric include universality, measurability, uniqueness and robustness. In addition, they have the inherent feature of vitality that signifies the life signs offering a strong protection against spoof attacks. Unlike conventional biometrics, the ECG or EEG is highly confidential and secure to an individual which is difficult to be forged. We present a review of methods used for the ECG and EEG as biometrics for individual authentication and compare their performance on the datasets and test conditions they have used. We illustrate the challenges involved in using the ECG or EEG as biometric primarily due to the presence of drastic acquisition variations and the lack of standardization of signal features. In order to determine the large-scale performance, individuality of the ECG or EEG is another challenge that remains to be addressed. Yogendra Narain Singh, Sanjay Kumar Singh, and Amit Kumar Ray Copyright © 2012 Yogendra Narain Singh et al. All rights reserved. Thu, 26 Jul 2012 07:49:46 +0000 http://www.hindawi.com/isrn/sp/2012/781653/ Image segmentation is a fundamental task for many computer vision and image processing applications. There exist many useful and reliable models for two-phase segmentation. However, the multiphase segmentation is a more challenging problem than two phase segmentation, mainly due to strong dependence on initialization of solutions. In this paper we propose a reliable hierarchical algorithm for multiphase texture image segmentation by making full use of two-phase texture models in a fuzzy membership framework. Application of the new algorithm to the synthetic and real medical imaging data demonstrate more satisfactory results than existing algorithms. Yalin Zheng and Ke Chen Copyright © 2012 Yalin Zheng and Ke Chen. All rights reserved. Tue, 10 Jul 2012 08:37:51 +0000 http://www.hindawi.com/isrn/sp/2012/714176/ Embedded block coding with optimised truncation (EBCOT) is a key algorithm in digital cinema (DC) distribution system. Though several high speed EBCOT architectures exist, all are not capable of meeting the DC specifications. To meet this challenge, the relationship between contents of a code block (CB) and context generation is studied. Our study reveals that it is difficult to predict number of contexts generated in a bit plane. Even the nature of number of contexts produced varies from CB to CB. In such a situation, it is difficult to ensure the frame rate requirement of DC. To avoid this uncertainty, a pass parallel, concurrent sample coding EBCOT architecture is proposed in this paper. It is capable of encoding one bit plane in 288 clock cycles under any circumstances. This design is prototyped on XC4VLX80-12 FPGA with multiple clock domains. After synthesizing, the bit plane coder (BPC) and MQ coder operate at 450 MHz and 123 MHz, respectively. In order to maintain synchronism among different clock domains, the BPC and MQ coder units are operated at 432 MHz and 108 MHz, respectively. This entails that the proposed design is capable of processing 2048×1080 size 57 DC frames in a second. Kishor Sarawadekar and Swapna Banerjee Copyright © 2012 Kishor Sarawadekar and Swapna Banerjee. All rights reserved. Sun, 08 Jul 2012 10:19:43 +0000 http://www.hindawi.com/isrn/sp/2012/625897/ The modified Riccati equation arises in the implementation of Kalman filter in target tracking under measurement uncertainty and it cannot be transformed into an equation of the form of the Riccati equation. An iterative solution algorithm of the modified Riccati equation is proposed. A method is established to decide when the proposed algorithm is faster than the classical one. Both algorithms have the same behavior: if the system is stable, then there exists a steady-state solution, while if the system is unstable, then there exists a critical value of the measurement detection probability, below which both iterative algorithms diverge. It is established that this critical value increases in a logarithmic way as the system becomes more unstable. Nicholas Assimakis and Maria Adam Copyright © 2012 Nicholas Assimakis and Maria Adam. All rights reserved. Thu, 28 Jun 2012 10:14:03 +0000 http://www.hindawi.com/isrn/sp/2012/584941/ Cognitive radio (CR) is considered nowadays as a strong candidate solution for the spectrum scarcity problem. On standards level, many cognitive radio standards have chosen Non-Contiguous Orthogonal Frequency Division Multiplexing (NC-OFDM) as their modulation scheme. Similar to OFDM, NC-OFDM suffers from the problem of having a high Peak to Average Power Ratio (PAPR). If not solved, either the transmitted signal will be distorted, which will cause interference to primary (licensed) users, or the effeciency of the power amplifier will be seriously degraded. The effect of the PAPR problem in NC-OFDM based cognitive radio networks is worse than normal OFDM systems. In this paper, we propose enhanced techniques to reduce the PAPR in NC-OFDM systems. We start by showing that combining two standard PAPR reduction techniques (interleaver-based and selective mapping) results in a lower PAPR than using them individually. Then, an “adaptive number of interleavers” will be proposed that achieves the same performance of conventional interleaver-based PAPR reduction while reducing the CPU time by 41.3%. Finally, adaptive joint interleaver with selective mapping is presented, and we show that it gives the same performance as conventional interleaver-based technique, with reduction in CPU time by a factor of 50.1%. Hefdhallah Sakran, Omar Nasr, and Mona Shokair Copyright © 2012 Hefdhallah Sakran et al. All rights reserved. Thu, 28 Jun 2012 08:47:08 +0000 http://www.hindawi.com/isrn/sp/2012/643563/ Identification of a signal component with the frequency exceeding the Nyquist limit is a challenging problem in signal theory as well as in some specific applications areas like astronomy and biosciences. A consequence of the well-known sampling theorem for a uniformly sampled signal is that the spectral component above the Nyquist limit is aliased into lower frequency range, making a distinction between true and aliased components impossible. The nonuniform sampling, however, offers a possibility to reduce aliased components and uncover information above the Nyquist limit. In this paper, we provide a theoretical analysis of the aliased components reduction in the nonparametric periodogram for two sampling schemes: the random sampling pattern and the sampling pattern generated by the integral pulse frequency modulation (IPFM), the latter widely accepted as the heart rate timing model. A general formula that relates the variance of timing deviations from a regular scheme with the aliased component suppression is proposed. The derived relation is illustrated by Lomb-Scargle periodograms applied on simulated data. Presented experimental data consisting of the respiration signal derived from the electrocardiogram and the heart rate signal also support possibility to detect frequencies above the Nyquist limit in the condition known as the cardiac aliasing. Jozef Púčik, Oldřich Ondráček, and Elena Cocherová Copyright © 2012 Jozef Púčik et al. All rights reserved. Tue, 19 Jun 2012 09:56:48 +0000 http://www.hindawi.com/isrn/sp/2012/631873/ This paper investigates the characteristics of the Kalman filter for a broad class of complex Fibonacci systems and represents an extension to the complex domain of the state estimation problem for the real-valued Fibonacci system. Complex Fibonacci systems are obtained by modifying the real-valued Fibonacci recurrence relation to include complex coefficients, control and noise inputs, and a noisy output-measurement equation. Analytic expressions for the Kalman filter’s steady-state gain and error covariance matrices are obtained, and it is found that for a broad subclass of these complex systems the elements of the matrices are functions of the golden ratio. John Donoghue Copyright © 2012 John Donoghue. All rights reserved. Thu, 31 May 2012 11:29:25 +0000 http://www.hindawi.com/isrn/sp/2012/805346/ This paper presents a new sample-level filtering order for the Deblocking Filter process of the H.264/AVC video coding standard to be used instead of the traditional block-level order presented in previous works. This processing order allows a better exploration of the parallelism in the filtering process by reducing data dependencies in comparison to other works. The proposed sample-level order allows four parallel and independent samples filtering simultaneously, completing one complete macroblock filtering in fewer cycles and requiring less memory space than the related works. The proposed filtering order can be applied to the Deblocking Filter presented in a conventional H.264/AVC encoder or decoder and to the H.264/SVC interlayer Deblocking Filter. When compared to the original H.264/AVC filter and to the best related work found in the literature, the proposed scheme achieves a reduction of 72% and 25% in the number of clock cycles and a memory usage decrease of 75% and 43%, respectively. Guilherme Correa, Luciano Agostini, and Luis A. da Silva Cruz Copyright © 2012 Guilherme Correa et al. All rights reserved. Thu, 17 May 2012 10:23:46 +0000 http://www.hindawi.com/isrn/sp/2012/914232/ Segmentations of medical images are required in a number of medical applications such as quantitative analyses and patient-specific orthotics, yet accurate segmentation without significant user attention remains a challenge. This work presents a novel segmentation algorithm combining the region-growing Seeded Cellular Automata with a boundary term based on an edge-detected image. Both single processor and parallel processor implementations are developed and the algorithm is shown to be suitable for quick segmentations (2.2 s for 256×256×124 voxel brain MRI) and interactive supervision (2–220 Hz). Furthermore, a method is described for generating appropriate edge-detected images without requiring additional user attention. Experiments demonstrate higher segmentation accuracy for the proposed algorithm compared with both Graphcut and Seeded Cellular Automata, particularly when provided minimal user attention. Ryan A. Beasley Copyright © 2012 Ryan A. Beasley. All rights reserved. Wed, 07 Mar 2012 09:28:44 +0000 http://www.hindawi.com/isrn/sp/2012/386505/ A feature extraction algorithm is introduced for face recognition, which efficiently exploits the local spatial variations in a face image utilizing curvelet transform. Although multi-resolution ideas have been profusely employed for addressing face recognition problems, theoretical studies indicate that digital curvelet transform is an even better method due to its directional properties. Instead of considering the entire face image, an entropy-based local band selection criterion is developed for feature extraction, which selects high-informative horizontal bands from the face image. These bands are segmented into several small spatial modules to capture the local spatial variations precisely. The effect of modularization in terms of the entropy content of the face images has been investigated. Dominant curvelet transform coefficients corresponding to each local region residing inside the horizontal bands are selected, based on the proposed threshold criterion, as features, which not only drastically reduces the feature dimension but also provides high within-class compactness and high between-class separability. A principal component analysis is performed to further reduce the dimensionality of the feature space. Extensive experimentation is carried out upon standard face databases and a very high degree of recognition accuracy is achieved even with a simple Euclidean distance based classifier. Hafiz Imtiaz and Shaikh Anowarul Fattah Copyright © 2012 Hafiz Imtiaz and Shaikh Anowarul Fattah. All rights reserved.