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Signal Processing (CIWSP 2013), 2013 Constantinides International Workshop on

Date 25-25 Jan. 2013

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Displaying Results 1 - 23 of 23
  • Table of content

    Publication Year: 2013 , Page(s): 1
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (39 KB)  

    The following topics are dealt with: filter bank; particle filter; fast resampling scheme; discrete Gould transform; H.264 region-based weighted prediction; video sequence; motion synthesis; hybrid binarisation technique; Bi-CoPaM method; MFCC feature extraction; subband-based joint blind source separation; kernel discriminant analysis; face recognition; image retrieval; image texture; direction-of-arrival estimation; ultrasound video despeckle filtering; video coding; amplify-and-forward transmission; nonlinear amplifier; intelligent digital filter; and MR brain image. View full abstract»

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  • Cascade of perfect reconstruction analysis and synthesis filter banks: The new architecture of next generation wideband receivers

    Publication Year: 2013 , Page(s): 1 - 8
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (456 KB)  

    We present here an innovative new receiver architecture with extreme computational efficiency that performs the multitude of DSP processing tasks required in a modern high bandwidth receiver with significantly reduced computational resources and with commensurate reduced power supply requirements. The system uses a pair of M-path perfect reconstruction polyphase filter banks to first form an input analysis filter bank and an output synthesis filter bank. The signal processing that implement the various signal processing tasks are applied as frequency dependent gains and additive corrections to the intermediate narrow band, reduced sample rate, time series residing between the analysis and synthesis filter banks. Sets of frequency dependent weights that represent each filtering task can simultaneously implement a channelizer, a matched filter, an equalizer, an intrusion canceller, an I-Q balancer, timing clock alignment, and carrier frequency and phase alignment. View full abstract»

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  • A fast resampling scheme for particle filters

    Publication Year: 2013 , Page(s): 1 - 4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (609 KB)  

    An unbiased resampling method is proposed for particle filters which is computing fast for implementation. There are two differences of our approach from other methods. First, the number of the particles is not fixed but varies around a reference. Second, it is a deterministic sampling procedure since there is no random numbers used. The core idea is simply replicating each particle as many times as the rounding result on the product of the reference number and weight of the particle. As an extension, the application of random numbers in resampling is discussed. Simulations show that our approach obtains comparable estimation accuracy with traditional resampling methods but be faster. View full abstract»

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  • Discrete Gould transform - Fast realisations and data hiding

    Publication Year: 2013 , Page(s): 1 - 4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (833 KB)  

    The computational complexity of the discrete Gould transform (DGT) is studied and a fast realisation approach is proposed. The reversible difference expansion data hiding method is applied to the DGT coefficients and experimental results are given. View full abstract»

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  • H.264 region-based weighted prediction for scenes with local brightness variations

    Publication Year: 2013 , Page(s): 1 - 4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (254 KB)  

    This paper presents a novel region-based weighted prediction (WP) parameter estimation scheme for H.264 to encode scenes with local brightness variations (LBV). The scheme is achieved by utilizing multiple WP parameter sets for various regions and assigning them to the same reference frame. These multiple WP parameter sets are then encoded using the framework of multiple reference frame motion estimation (MRFME). This arrangement ensures that the proposed scheme is compliant with the H.264 standard. In this scheme, a region partitioning process is designed to divide the current frame into different regions where each one has some degree of uniformity in its brightness variation. This can assist in estimating multiple sets of region-based WP parameters accurately. As a consequence, the proposed scheme can improve prediction in scenes with different degrees of LBVs in different regions of the same picture. Results show that the region-based scheme can efficiently handle LBV scenes with significant coding gain. View full abstract»

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  • Splicing partial body motion video sequences for motion synthesis

    Publication Year: 2013 , Page(s): 1 - 4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (289 KB)  

    Motion synthesis has become an important research area in computer animation. When synthesizing new motions, recent partial body parts motion synthesis methods allow two upper body motions to be swapped if they have similar lower body motion. Although such requirement can ensure natural motion, it limits the possibility of new motions that can be synthesized using this method. In this paper, we propose to relax this requirement by considering also lower body motions that have only similar functionality and regularity. To facilitate the similarity measurement, a new time alignment algorithm is proposed so that motion sequences which have similar regularity can be easily identified. Our results show that the proposed algorithm can significantly improve the reusability of motion data for motion synthesis. View full abstract»

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  • Hybrid binarisation technique for the Bi-CoPaM method

    Publication Year: 2013 , Page(s): 1 - 4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (98 KB)  

    A relaxed paradigm of clustering has been proposed recently in which each data object can be assigned exclusively to one cluster, assigned simultaneously to multiple clusters, or unassigned from all clusters. This has been realised by six tunable binarisation techniques for the binarisation of consensus partition matrices (Bi-CoPaM) ensemble clustering method. These techniques can be used to generate clusters with tunable tightness levels from wide clusters, through complementary clusters and towards tight clusters. In this study, we analyse these six techniques and classify them into two classes/tracks which differ in the way in which they gradually tighten clusters. We also propose using hybrid combinations of the techniques from both classes/tracks. The results of applying these techniques over a real microarray dataset of 1000 yeast genes demonstrate that, in many cases, there are significant differences between both classes/tracks of techniques. Moreover, comparisons between both classes/tracks by hybrid combinations are able to unveil information about the distinctness of the clusters and the competitiveness between them. View full abstract»

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  • Joint user scheduling, link adaptation and space division multiplexing for the uplink of multi-cell distributed antenna systems with imperfect CSI

    Publication Year: 2013 , Page(s): 1 - 4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (194 KB)  

    This paper proposes a joint user scheduling, linkadaptation and space division multiplexing algorithm for the up-link of distributed antenna systems (DASs) in a multi-cell scenario. Link adaptation includes power control and adaptive modulation and coding (AMC). The algorithm is based on an iterative least squares (LS) optimization, where power levels and beam-forming vectors are jointly calculated so as to comply with a different SINR (signal-to-interference-plus-noise ratio) for each scheduled user. This SINR level ensures the transmission of the selected modulation and coding scheme (MCS) with a value of BLER (block error rate). Whenever the SINR requirements are not met, then AMC and user scheduling are smoothly enabled so as to continue with another LS stage for further optimization. Each LS stage is solved by the method of gradient steepest descent, whose convergence speed is improved by reusing the solution of previous LS stages. An additional iterative loop is also used for a more efficient calculation of inter-cell interference. Imperfect channel state information is used throughout all system-level simulations. Results show considerable throughput gains when compared to conventional approaches. View full abstract»

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  • Packet loss concealment by interpolation for speech over IP network services

    Publication Year: 2013 , Page(s): 1 - 4
    Cited by:  Papers (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (705 KB)  

    This paper presents a packet loss concealment (PLC) method based on interpolation by separation odd and even frames to improve speech quality deterioration caused by packet losses for CELP based coders. We applied our scheme to the standard ITU-T G.729 speech coder to evaluate the proposed method. The perceptual evaluation of speech quality (PESQ) and enhanced modified bark spectral distortion (EMBSD) tests under various packet loss conditions confirm that the proposed algorithm is superior to the concealment algorithm embedded in the G.729. The performance measures prove that our concealment method based interpolation is better. View full abstract»

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  • Empirical Mode Decomposition VAD based on multiple sensor LRT

    Publication Year: 2013 , Page(s): 1 - 4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (120 KB)  

    Voice Activity Detection (VAD) remains a challenging task given its dependence on adverse noise and reverberation conditions. The problem becomes even more difficult when the microphones used to detect speech reside far from the speaker. In this paper, an unsupervised VAD scheme is presented, based on the Empirical Mode Decomposition (EMD) analysis framework and a multiple input likelihood ratio test (LRT). The highly efficient method of EMD relies on local characteristics of time scale of the data to analyse and decompose non-stationary signals into a set of so called intrinsic mode functions (IMF). These functions are injected to the multiple input LRT scheme in order to decide upon speech presence or absence. To minimize mis-detections and enhance the performance of the hypothesis test, a computationally efficient forgetting scheme along with an adaptive threshold are also employed. Simulations, conducted in several artificial environments, illustrate that significant improvements can be expected, in terms of performance, from the proposed scheme when compared to similar VAD systems. View full abstract»

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  • Efficient MFCC feature extraction on Graphics Processing Units

    Publication Year: 2013 , Page(s): 1 - 4
    Cited by:  Papers (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (185 KB)  

    In this paper, we present an efficient parallel implementation of Mel-frequency Cepstral Coefficient (MFCC)-based feature extraction and describe the optimizations required for effective throughput on Graphics Processing Units (GPU) processors. We demonstrate that the feature extraction process in automatic speech recognition is well suited for GPUs and a substantial reduction in computation time can be obtained by performing feature extraction on these platforms. Using a single Nvidia GTX580 GPU our proposed approach is shown to be approximately 90x faster than a sequential CPU implementation, enabling feature extraction to be performed at under 0.01% real-time. This is significantly faster than prior reported results implemented on GPUs, DSPs and FPGAs. Furthermore we demonstrate that multiple MFCC features can be generated for a set of predefined Vocal-Tract-Length-Normalization (VTLN) alpha parameters with little degradation in throughput. Using the approach described in this paper MFCC features were extracted in 0.05% and 0.09% realtime, for 11 and 21 VTLN parameters respectively. View full abstract»

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  • Outage analysis of multi-relay selection in underlay cognitive AF relay networks

    Publication Year: 2013 , Page(s): 1 - 4
    Cited by:  Papers (1)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (155 KB)  

    We evaluate the outage probability of cognitive amplify-and-forward relay networks with cooperation between certain secondary users chosen by multi-relay selection based on the underlay approach, while adhering to the interference constraint on the primary user. A max-min strategy is employed to perform best relay or multi-relay, i.e. between two and four relays, selection. We obtain analytical expressions for the probability density function (PDF), and cumulative density function (CDF) of the received signal-to-noise ratio (SNR) and thereby provide near closed form expressions for outage probability over Rayleigh frequency flat fading channels, which are verified by numerical simulation. View full abstract»

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  • Subband-based joint blind source separation for convolutive mixtures employing M-CCA

    Publication Year: 2013 , Page(s): 1 - 4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (264 KB)  

    This paper addresses the source separation problem for convolutive mixtures by employing the joint blind source separation (BSS) technique in the subband domain. The key to the proposed method is to decompose the time-domain mixed signals into subbands to generate the required related multiple data sets for the operation of joint BSS. To reduce the aliasing error after subband decimation, the oversampled generalized DFT filter banks are employed to maintain a sufficient level of correlation between the data sets. A recently proposed correlation optimisation method for the design of filter banks is adopted to enhance the correlation between adjacent subband signals, which leads to further improved separation results in terms of both signal to interference ratio and subband permutation alignment. View full abstract»

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  • Massively parallel time-stretched analog-to-digital converter

    Publication Year: 2013 , Page(s): 1 - 4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (809 KB)  

    Time interleaving is an effective method for increasing the sampling rate of electronic analog-to-digital converters (ADCs). The main artifact of time-interleaved ADC (TI-ADC) is caused by mismatches between different sub-ADC channels. The mismatches include mismatches in gain, bandwidth, and frequency response. The ultimate achievable bandwidth of the TI-ADC is limited by the bandwidth of the sample-and-hold (S/H). Currently, the bandwidth of S/H constructed using electronic transistor is limited to the lower tens of GHz range. To increase the bandwidth of ADC into the upper tens of GHz range and beyond, incorporating photonic preprocessor becomes the natural choice. In this paper, we present our efforts on the implementation of a massively parallel TI-ADC with photonic preprocessor. In our system, the input signal is sampled using a mode-lock laser. The sampled pulses are stretched in optical fiber until they are long enough to be sampled by a massive array of 2 Giga-samples per second (GS/s) electronic ADC. View full abstract»

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  • Contextual constraints based kernel discriminant analysis for face recognition

    Publication Year: 2013 , Page(s): 1 - 4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (210 KB)  

    This paper proposes a two-step subspace learning framework by combining non-linear kernel PCA (KPCA) and with contextual constraints based linear discriminant analysis (CCLDA) for face recognition. The linear CCLDA approach does not consider the higher order non-linear information in facial images, whereas the wide face variations posed by some factors, such as viewpoint, illumination and expression, existing in nonlinear subspaces may lead to many difficulties in face recognition and classification problems. To counteract the above problem, we incorporate the contextual information into kernel discriminant analysis by using KPCA in a two-step process, which provides more useful information for face recognition and classification. Experimental results on three well-known face databases, ORL, Yale and XM2VTS, validate the effectiveness of the proposed method. View full abstract»

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  • Universal approach for estimating unknown frequencies for unknown number of sinusoids in a signal

    Publication Year: 2013 , Page(s): 1 - 4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (238 KB)  

    This paper presents a new approach to estimate the unknown frequencies of the constituent sinusoids in a noiseless signal. The signal comprising of unknown number of sinusoids of unknown amplitudes and unknown phases is measured in the time domain. The Hankel matrix of measured samples is used as a basis for further analysis in the Pisarenko harmonic decomposition. A new constraint, the Existence Factor (EF), has been introduced in the methodology based on the relationship between the frequencies of the unknown sinusoids and the eigenspace of Hankel matrix of signal's samples. The accuracy of the method has been tested through multiple simulations on different signals with an unknown number of sinusoidal components. Results showed that the proposed method has efficiently estimated all the unknown frequencies. View full abstract»

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  • Content Based Image Retrieval by combining color, texture and CENTRIST

    Publication Year: 2013 , Page(s): 1 - 4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (841 KB)  

    This paper presents a novel framework for Content Based Image Retrieval(CBIR), which combines color, texture and spatial structure of image. The proposed method uses color, texture and spatial structure descriptors to form a feature vector. Images are segmented into regions to extract local color, texture and CENTRIST(CENsus Transform hISTogram) features respectively. Multiple-instance learning (MIL) and Diverse Density(DD) are incorporated with regions as instances to find the objective instance. In addition, to denote the whole structure of image better, we perform PCA to CENTRIST features of all images, i.e. spatial Principal component Analysis of Census Transform(spatial PACT). This framework integrates three features to enhance the retrieval performance. Experiments on COREL standard database invalidate the proposed method by comparing with some state-of-the-art methods. View full abstract»

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  • Visual analysis for semantic search in digital libraries

    Publication Year: 2013 , Page(s): 1 - 4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (143 KB)  

    Semantic search of cultural content is of major importance in current cultural digital libraries, such as Europeana, or the evolving Digital Public Library of America. Content metadata accompanying the digitised items are analysed, mapped and used to interpret users' queries, so that the most appropriate content is selected and presented to them. Multimedia, especially automatic visual analysis, has not been a main component yet. This paper presents a semantic search methodology, including a query answering mechanism which meets the semantics of users' queries and enriches the answers by exploiting appropriate local (SURF) and global (MPEG-7) visual features and descriptors. An experimental study is presented, using content from the Europeana digital library, involving both thematic knowledge and visual analysis of cultural images, illustrating the improved content search performance. View full abstract»

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  • Direction-of-arrival estimation in partially calibrated subarray-based MIMO radar

    Publication Year: 2013 , Page(s): 1 - 4
    Cited by:  Papers (2)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (219 KB)  

    The problem of direction-of-arrival (DOA) estimation in partially calibrated multi-input multi-output (MIMO) radar composed of multiple subarrays is studied. We assume that each subarray is calibrated well, so that the steering vectors of all subarrays are exactly known. However, the intersubarray parameters are completely/partly unknown. The proposed method first obtains a set of initial DOA results by employing a rotational invariance property between two sets of received data associated with the two calibrated antennas within the first subarray, and then more accurate DOA estimation is obtained by using the rank reduced estimator (RARE) through a local searching algorithm. We also derive the corresponding stochastic CramérRao bound (CRB) to which we compare the performance of the proposed estimator. View full abstract»

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  • Portable multi touch TableTop: A composite approach for industrial applications

    Publication Year: 2013 , Page(s): 1 - 4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (584 KB)  

    Digital tabletops are gaining increasing interest within commercial sectors both for home and office applications. These devices, with their multi-touch surfaces, can support collaborative activities while maintaining natural face-to-face communication. However, still one of the major problems is related to their portability and the space they require. We have conducted a study to explore how to design a novel architecture for surfaces that could operate in any environment without space limitations based on multiple tabletops. This paper presents an architecture based on the relative position of the tablets is proposed including an efficient data transmission system in order to obtain real time synchronisation and positioning of multiple tablets using a star topology. View full abstract»

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  • Ultrasound video despeckle filtering for High Efficiency Video Coding in m-health systems

    Publication Year: 2013 , Page(s): 1 - 4
    Cited by:  Papers (2)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (253 KB)  

    Mobile-Health (m-health) medical video communication systems need to communicate ultrasound video of adequate diagnostic quality for remote diagnosis and care. In this study, we demonstrate how ultrasound video noise reduction, employed as a pre-processing step, used in conjunction with High Efficiency Video Coding (HEVC), can significantly improve diagnostic quality at considerably lower bitrate demands than conventional H.264/AVC source encoding. Three video despeckle filters were investigated, namely: linear filtering (DsFlsmv), hybrid median filtering (DsFhmedian), and speckle reducing anisotropic diffusion (DsFsrad). The methods were tested using ten atherosclerotic plaque ultrasound videos. Speckle filtering was applied at a frame-level basis. Experimental results were obtained using both subjective (by two clinical experts) and objective video quality assessment. The best achieving despeckle filter was DsFlsmv followed closely by DsFhmedian. In both cases, the filters provided for increased clinical performance while associated with significant bitrate demands reductions. View full abstract»

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  • Estimation for amplify-and-forward transmissions with nonlinear amplifiers

    Publication Year: 2013 , Page(s): 1 - 4
    Cited by:  Papers (2)
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (867 KB)  

    This paper describes the development of a distributed estimation algorithm for amplify-and-forward sensor transmissions with realistic nonlinear amplifier models at the sensors. Specifically, an algorithm is developed that enables distributed estimation with amplifiers operating in the non-linear class AB region. In this system, a digital predistortion scheme is utilized to fit an amplifier to a mathematically tractable, known nonlinearity that is close to the compression characteristics of the amplifier. We show using this scheme has two benefits over linear amplifier operation: improved transmitter efficiency and reduced sensitivity to heavy-tailed distributions due to the soft saturation. The amplifier characteristics and predistortion methods are presented as part of the Java-DSP software package. View full abstract»

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  • Intelligent digital filters with application to salt and pepper noise reduction in MR brain images

    Publication Year: 2013 , Page(s): 1 - 4
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (613 KB)  

    This paper introduces intelligent digital filters and demonstrates its operations using a fuzzy-based intelligent digital filter with an application to salt and pepper noise reduction in magnetic resonance (MR) brain images. The fuzzy-based intelligent digital filter adopts an adaptive window size, a salt and pepper noise detector, and a novel membership function. It employs an information-to-coefficient processor for computing input-dependent filter coefficients and a fuzzy filter for time-varying digital filtering. Simulation results indicate that the filter is effective for reducing low to high density salt and pepper noise in MR brain images. Performance comparisons to the iterative median filter and the non-local means filter are included. View full abstract»

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