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Online ISSN 1751-9683 Print ISSN 1751-9675

IET Signal Processing

Volume 6, Issue 7, September 2012

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Volume 6, Issue 7

September 2012

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    • Improved normalised difference vegetation index method based on discrete cosine transform and singular value decomposition for satellite image processing
      • Author(s): A. Kumar ; A.K. Bhandari ; P. Padhy
      • Source: IET Signal Processing, Volume 6, Issue 7, p. 617 –625
      • DOI:  10.1049/iet-spr.2011.0298
      • Type: Article
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      • p. 617 –625 (9)
        In this study, an improved multi-band satellite contrast enhancement technique based on the singular value decomposition (SVD) and discrete cosine transform (DCT) has been proposed for the feature extraction of low-contrast satellite images using normalised difference vegetation index (NDVI) technique. The method employs multi-spectral remote sensing data technique to find the spectral signature of different objects such as the vegetation index and land cover classification presented in the satellite image. The proposed technique converts the image into the SVD–DCT domain and after normalising the singular value matrix; the enhanced image is reconstructed by using inverse DCT. The visual and quantitative results included in this study clearly show the increased efficiency and flexibility of the proposed method over the existing methods. The simulation results show that the enhancement-based NDVI using DCT–SVD technique is highly useful to detect the surface features of the visible area which are extremely beneficial for municipal planning and management.
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      Linear coherent distributed estimation with cluster-based sensor networks
      • Author(s): C.-A. Lin  and  C.-H. Wu
      • Source: IET Signal Processing, Volume 6, Issue 7, p. 626 –632
      • DOI:  10.1049/iet-spr.2011.0199
      • Type: Article
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      • p. 626 –632 (7)
        The authors consider distributed estimation using sensor network with coherent multiple access channel model and LMMSE fusion rule. The sensors in the network are divided into a number of clusters. Sensors within the same cluster are allowed to collaborate through an amplification matrix to form a message this then transmitted. They formulate the problem of choosing the amplification matrices as an optimal power allocation problem under a total power constraint. The solution gives the optimal amplification matrices as scaled outer products of the observation gain and the channel gain vectors. The authors show that collaboration improves performance and, in simulations, demonstrate that the amount of improvement is closely related to the amount of collaboration.
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      High-quality Laplacian source quantisation using a combination of restricted and unrestricted logarithmic quantisers
      • Author(s): Z. Peric  and  J. Nikolic
      • Source: IET Signal Processing, Volume 6, Issue 7, p. 633 –640
      • DOI:  10.1049/iet-spr.2011.0213
      • Type: Article
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      • p. 633 –640 (8)
        This study proposes a quantiser, named the combined quantiser, composed of two forward adaptive μ-law quantisers (FAμQs), one designed to quantise signals having restricted amplitude dynamics and the other designed for unrestricted signals. The combined quantiser performs frame-by-frame analysis of the input signal, according to which, for each frame procession, it selects one of the two disposable FAμQs. In order to exploit the higher density of the restricted FAμQ's quantisation levels, the restricted FAμQ is selected when all amplitudes of samples within a frame belong to the restricted FAμQ's support region. Otherwise, the unrestricted FAμQ having the same number of quantisation levels, but a wider support region is selected. To provide a more frequent selection of the restricted FAμQ than the unrestricted one, the disposable quantisers’ support region thresholds are determined to satisfy the total distortion minimisation criterion. The authors show that the combined quantiser designed for the Laplacian source provides gain in the signal to quantisation noise ratio and in the compression over the G.711 quantiser as well as satisfies G.712 Recommendation for high-quality quantisation. This indicates the possibility of practical application of the combined quantiser in the contemporary transmission of Laplacian source signals.
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      Stability of two-dimensional digital filters described by the Fornasini–Marchesini second model with quantisation and overflow
      Random finite sets-based joint manoeuvring target detection and tracking filter and its implementation
      • Author(s): Y. Wei ; F. Yaowen ; L. Jianqian ; L. Xiang
      • Source: IET Signal Processing, Volume 6, Issue 7, p. 648 –660
      • DOI:  10.1049/iet-spr.2011.0171
      • Type: Article
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      • p. 648 –660 (13)
        This study considers the problem of jointly detecting whether a target is present in a scene and estimating its state, if it is there. This joint detection and estimation problem can be solved using a special case of the multi-target Bayes filter (referred to as the joint target detection and tracking (JoTT) filter). However, if the model used by the JoTT filter does not match the actual dynamics, the filter will tend to miss-detection directly or diverge such that the actual errors fall outside the range predicted by the filter's estimate of the error covariance. A similar difficulty arises, if the target behaviour can switch between different modes of operation, since the filter may then be accurate for only one particular mode. This study proposes a novel joint detection and tracking filter, which is the multiple model extension of the JoTT filter to accommodate the possible target manoeuvring behaviour. In addition, a sequential Monte Carlo implementation (for generic models) and a Gaussian mixture implementation (for linear Gaussian models) are proposed. The simulation results are presented to show the effectiveness of the proposed filter over the original JoTT filter.
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      Hybrid parallel/cascade structure for designing variable fractional-delay filters
      • Author(s): S.-L. Lee
      • Source: IET Signal Processing, Volume 6, Issue 7, p. 661 –672
      • DOI:  10.1049/iet-spr.2011.0065
      • Type: Article
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      • p. 661 –672 (12)
        There are two different ways to implement variable fractional-delay (VFD) filters. One is the Farrow structure, which is constructed by connecting differentiators with various orders in parallel, the other one is the first-order differentiator structure, which is constructed by cascading first-order differentiators. The parallel Farrow structure requires a large memory to store filter coefficients but possesses low filter delay, and the cascade first-order differentiator structure requires less memory but results in long filter delay. In this study, a hybrid structure is presented to implement the VFD filter, which considers the parallel and cascade connections of differentiators simultaneously such that the trade-off between memory requirement and filter delay can be made. Some numerical examples are demonstrated to show the effectiveness of the proposed structure.
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      Bayesian recovery of sinusoids from noisy data with parallel tempering
      • Author(s): M. Cevri  and  D. Üstündağ
      • Source: IET Signal Processing, Volume 6, Issue 7, p. 673 –683
      • DOI:  10.1049/iet-spr.2011.0335
      • Type: Article
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      • p. 673 –683 (11)
        This study deals with parameter estimation of sinusoids within a Bayesian framework, where inferences about the parameters require an evaluation of complicated high-dimensional integrals and a solution of multi-dimensional optimisation of their posterior probability density function (PDF) under a combination of different prior PDFs of parameters. In this context, the authors make an attempt to improve an efficient stochastic procedure based on a parallel tempering Markov chain Monte Carlo sampler with a proposal distribution whose width varies with a Cramér–Rao lower bound (CRLB), known as a lower limit on variance of any unbiased estimator. Its algorithm is coded in ‘Mathematica’, which provides a much flexible and efficient computer programming environment. Computer simulations are included to corroborate theoretical developments and to compare the estimator performance with the CRLB for different length of data sampling and signal-to-noise ratio (SNR) conditions. Therefore all simulations support its effectiveness and demonstrate its performance in terms of CRLB for sufficiently high-SNR and short data lengths.
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      Generation of coloured acoustic noise samples with non-Gaussian distributions
      • Author(s): L. Zão  and  R. Coelho
      • Source: IET Signal Processing, Volume 6, Issue 7, p. 684 –688
      • DOI:  10.1049/iet-spr.2011.0216
      • Type: Article
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      • p. 684 –688 (5)
        This study proposes a method for generating acoustic noise sequences with different distributions and coloured spectra. The noise samples are obtained by passing a non-Gaussian white noise through a finite impulse response filter. The resulting power spectral density is proportional to 1/fβ, where β is a positive power-law exponent. The noise samples pattern is determined by the Kurtosis ratio. The proposed generator is evaluated by comparing real and artificial acoustic noises statistics in the time and frequency domains. The results show that the generated coloured sequences achieved the PSD decaying rate and also the non-Gaussian pattern of the real environmental acoustic noises.
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      Source enumeration in large arrays using moments of eigenvalues and relatively few samples
      • Author(s): E. Yazdian ; S. Gazor ; H. Bastani
      • Source: IET Signal Processing, Volume 6, Issue 7, p. 689 –696
      • DOI:  10.1049/iet-spr.2011.0260
      • Type: Article
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      • p. 689 –696 (8)
        This study presents a method based on minimum description length criterion to enumerate the incident waves impinging on a large array using a relatively small number of samples. The proposed scheme exploits the statistical properties of eigenvalues of the sample covariance matrix (SCM) of Gaussian processes. The authors use a number of moments of noise eigenvalues of the SCM in order to separate noise and signal subspaces more accurately. In particular, the authors assume a Marcenko–Pastur probability density function (pdf) for the eigenvalues of SCM associated with the noise subspace. We also use an enhanced noise variance estimator to reduce the bias leakage between the subspaces. Numerical simulations demonstrate that the proposed method estimates the true number of signals for large arrays and a relatively small number of snapshots. In particular, the proposed method requires less number of samples to achieve the same correct enumeration probability compared to the state-of-the-art methods. The authors evaluated the assumed pdf in order to justify the limitation and the behaviour of the proposed method for small number of snapshots and array sizes.
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      Parameter-dependent mixed ℋ2/ℋ∞ filtering for linear parameter-varying systems
      • Author(s): H. Zhang ; Y. Shi ; A.S. Mehr
      • Source: IET Signal Processing, Volume 6, Issue 7, p. 697 –703
      • DOI:  10.1049/iet-spr.2011.0088
      • Type: Article
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      • p. 697 –703 (7)
        In this study, the authors deal with the mixed ℋ2/ℋ∞ filtering problem for continuous-time systems. The system model is subject to parameter variation and the parameters of the model vary slowly in the polytope. The parameters of the designed filter are dependent on variation, which is measured online. A new design approach is proposed by increasing the flexible dimensions in the solution space. An illustrative example shows the new features of the proposed design approach.
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      Polynomial matrix QR decomposition for the decoding of frequency selective multiple-input multiple-output communication channels
      • Author(s): J. Foster ; J. McWhirter ; S. Lambotharan ; I. Proudler ; M. Davies ; J. Chambers
      • Source: IET Signal Processing, Volume 6, Issue 7, p. 704 –712
      • DOI:  10.1049/iet-spr.2011.0086
      • Type: Article
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      • p. 704 –712 (9)
        This study proposes a new technique for communicating over multiple-input multiple-output (MIMO) frequency selective channels. This approach operates by calculating the QR decomposition of the polynomial channel matrix at the receiver on the basis of channel state information, which in this work is assumed to be perfectly known. This then enables the frequency selective MIMO system to be transformed into a set of frequency selective single-input single-output systems without altering the statistical properties of the receiver noise, which can then be individually equalised. A like-for-like comparison with the orthogonal frequency division multiplexing scheme, which is typically used to communicate over channels of this form, is provided. The polynomial matrix system is shown to achieve improved performance in terms of average bit error rate results, as a consequence of time-domain symbol decoding.
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