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Signal Processing, IET

Issue 7 • Date Oct. 2011

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Displaying Results 1 - 9 of 9
  • Objective quality measures for perceptual evaluation in digital audio watermarking

    Page(s): 623 - 631
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (314 KB)  

    In this study, objective quality measures adopted in speech processing are proposed to evaluate the perceptual quality of the watermarked audio signals. Under different audio watermarking techniques such as spread spectrum watermarking, cepstrum domain watermarking, wavelet domain watermarking, echo hiding and histogram-based watermarking, the dissimilarities between the watermarked and host audio signals are separately quantified in terms of several well-developed quality measures, including the signal-to-noise ratio (SNR), the segmental SNR (segSNR), the cepstral distortion (CD), the log-likelihood ratio (LLR), the Itakura-Saito (IS) distortion, the log-area ratio (LAR) and the weighted spectral slope (WSS) measures. For correlation analysis, subjective listening tests and a commercial evaluation tool -Perceptual Model-Quality Assessment- (PEMO-Q) are also used to grade the differences. Two types of Pearson-s correlation coefficients, that is, average and overall correlation coefficients, are calculated to evaluate the performance of quality measures serving as the predictors of perceptual quality. Extensive experiments indicate that there is a good correlation between the investigated quality measures and subjective difference grades. Specifically, the LAR and LLR measures yield the highest average and overall correlation coefficients for most audio watermarking techniques. Moreover, a large decrease in computation time reveals that quality measures run much faster than PEMO-Q. It is therefore concluded that quality measures can be used for objective assessment of the perceptual quality in audio watermarking. View full abstract»

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  • Stepped-frequency inverse synthetic aperture radar imaging based on adjacent pulse correlation integration and coherent processing

    Page(s): 632 - 642
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (765 KB)  

    The high range resolution profile (HRRP) can be reconstructed by combining frequency bands coherently for inverse synthetic aperture radar (ISAR) imaging of a moving target in stepped-frequency (SF) radar systems. However, the range migration and phase errors among sub-pulses in a pulse train caused by the target translational motion results in difficulty for HRRP synthesis of SF sub-pulses. In order to compensate the translational motion for SF ISAR imaging, a novel method based on adjacent pulses correlation integration and coherent processing is proposed in this study. Firstly, the radial motion parameters can be estimated by the adjacent pulses correlation integration for the range echo envelope in a pulse train. Owing to strong coherence between two adjacent pulses, the correlation integration achieves high gain of signal-to-noise ratio. It is robust to noise ensuring precise estimation of translational motion. Secondly, after compensating the phase errors, the HRRP can be reconstructed by the combination of frequency bands coherently and the inverse Fourier transform. Finally, a nice ISAR image of a moving target can be obtained by conventional range-Doppler algorithm (RDA). In the end, simulated and real data are used to demonstrate the good performance of the method proposed in this study. View full abstract»

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  • Joint complex diversity coding and channel coding over space, time and frequency

    Page(s): 643 - 651
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (558 KB)  

    This study provides a general diversity analysis for joint complex diversity coding (CDC) and channel coding-based space-time-frequency codeing is provided. The mapping designs from channel coding to CDC are crucial for efficient exploitation of the diversity potential. This study provides and proves a sufficient condition of full diversity construction with joint three-dimensional CDC and channel coding, bit-interleaved coded complex diversity coding and symbol-interleaved coded complex diversity coding. Both non-iterative and iterative detections of joint channel code and CDC transmission are investigated. The proposed minimum mean-square error-based iterative soft decoding achieves the performance of the soft sphere decoding with reduced complexity. View full abstract»

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  • Constructing n-cell numbers by using double-side separation degrees and pattern recognition based on the maximal membership principle

    Page(s): 652 - 661
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (201 KB)  

    In this study, by using both the left and right separation degrees, the authors establish a method constructing fuzzy n-cell numbers to express uncertain or imprecise multi-channel digital signals. They conclude that the maximal membership method can be adopted to identify an object in some precise or certain environment. Moreover, the authors point out that the method based on the maximal membership possesses some weaknesses, and introduce the concept of p-membership function to overcome the shortcomings, thus using the maximal p-membership principle to identify an object. View full abstract»

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  • Superimposed event detection by particle filters

    Page(s): 662 - 668
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (279 KB)  

    In this study, the authors consider online detection and separation of superimposed events by applying particle filtering. They observe only a single-channel superimposed signal, which consists of a background signal and one or more event signals in the discrete-time domain. It is assumed that the signals are statistically independent and can be described by random processes with known parametric models. The activation and deactivation times of event signals are assumed to be unknown. This problem can be described as a jump Markov system (JMS) in which all signals are estimated simultaneously. In a JMS, states contain additional parameters to identify models. However, for superimposed event detection, the authors show that the underlying JMS-based particle-filtering method can be reduced to a standard Markov chain method without additional parameters. Numerical experiments using real-world sound processing data demonstrate the effectiveness of their approach. View full abstract»

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  • Performance analysis of a bayesian classifier for the detection of human presence using total power and correlation radiometry

    Page(s): 669 - 679
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (745 KB)  

    This study presents a performance analysis of a new method of detecting and classifying non-moving humans from a moving platform in real time using millimetre-wave radiometry. The implementation of the detection method is a naïve Bayes classifier which operates on signals produced by two Ka-band total power receivers, one W-band total power receiver and one Ka-band correlation receiver. Processing of the radiometric signals involves median filtering and passive range estimation prior to the signals being classified by the Bayesian algorithm. Experimental results are shown and a performance evaluation of the classifier is given using the F1-measure and the receiver operating characteristic. A maximum F1-measure of 0.68 is achieved, and the area under the receiver operating curve is 0.94 and 0.98 for passive and active ranging, respectively. The maximum true positive rate was 0.85 (passive) and 0.92 (active) both corresponding to F1=0.48. The processing time required for classification is shown to be less than 50= of the experimental time, permitting real-time operation. View full abstract»

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  • Experimental analysis of various estimators for target range estimation in high resolution radars

    Page(s): 680 - 689
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (429 KB)  

    The author analyses the target range estimation errors in pulse compression high-resolution radars (HRRs). Conventional radar signal processors assume a point target model in matched filtering-based detection and tracking. The author demonstrates through simulations that the performance degradation, under the point target assumption, can be significant for HRRs, where targets extend across several detection cells. Also, the author models events of backscatters from illuminated target and clutter as a non-homogenous Poisson process (NHPP). The corresponding maximum likelihood, maximum a posteriori, minimum mean square error and minimum mean absolute error estimators are derived for range estimation. Typical target detection process has been simulated and the performance of NHPP-based estimators has been compared to that of the most commonly used peak estimators, namely, the maximum point and interpolation peak estimators. Simulation results show that the proposed estimators significantly reduce target range estimation errors in HRRs. View full abstract»

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  • Multifractality and singularity of 8b solar neutrino flux signals from sudbury neutrino observatory

    Page(s): 690 - 700
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (970 KB)  

    The authors have investigated two solar neutrino flux time series data from Sudbury Neutrino Observatory: one is that with D2O and another is with salt. Both these data series being complex, non-linear and non-stationary, the authors have tried to detect the irregularity and multifractality in them using multifractal detrended fluctuation analysis and comparing with the results obtained using wavelet transform modulus maxima algorithm. Singularity spectra of the signals have been obtained to measure the degree of multifractality of the solar neutrino flux signal. View full abstract»

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  • Switched adaptive quantiser for speech compression based on optimal companding and correlation

    Page(s): 701 - 707
    Save to Project icon | Click to expandQuick Abstract | PDF file iconPDF (408 KB)  

    This study describes a novel adaptive quantiser based on the optimal companding technique. Adaptation is achieved by adjusting the input of the fixed or non-adaptive quantiser according to the estimated and quantised gain on each particular frame. In such a way better quantiser adaptation to the varying input statistics is provided. Selection of the appropriate bit rate is performed depending on the value of the correlation coefficient ρ on each frame. The decision thresholds for ρ are determined under the condition that the signal to quantisation noise ratio does not drop under 34.3ρdB, satisfying the G.712 standard quality of speech, while decreasing the bit rate. The information about the gain and about the chosen bit rate is then transferred as a side information to a decoder. Although this slightly increases the side information, the overall savings in the bit rate have shown to be substantial. Theoretical and experimental results are provided, which point out the benefits that can be achieved using the proposed algorithm. View full abstract»

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