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  • 1.
    Anderson, Sören
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    On Optimal Dimension Reduction for Sensor Array Signal Processing1993In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 30, no 2, p. 245-256Article in journal (Refereed)
    Abstract [en]

    The computational complexity for direction-of-arrival estimation using sensor arrays increases very rapidly with the number of sensors in the array. One way to lower the amount of computations is to employ some kind of reduction of the data dimension. This is usually accomplished by employing linear transformations for mapping full dimension data into a lower dimensional space. Different approaches for selecting these transformations have been proposed. In this paper, a transformation matrix is derived that makes it possible to theoretically attain the full-dimension Cramér-Rao bound also in the reduced space. A bound on the dimension of the reduced data set is given, above which it is always possible to obtain the same accuracy for the estimates of the source localizations, using the lower-dimension data, as that achievable by using the full dimension data. Furthermore, a method is devised for designing the transformation matrix. Numerical examples, using this design method, are presented, where the achievable performance of the (optimal) Weighted Subspace Fitting method with full dimension data is compared to the performance obtained with reduced dimension data. The problem of estimating parameters of sinusoidal signals from noisy data is also addressed by a direct application of the results derived herein.

  • 2.
    Andersson, Kenneth
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Westin, Carl-Fredrik
    Laboratory of Mathematics in Imaging, Harvard Medical School, Brigham and Women's Hospital, Boston, USA.
    Knutsson, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, The Institute of Technology.
    Prediction from off-grid samples using continuous normalized convolution2007In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 87, no 3, p. 353-365Article in journal (Refereed)
    Abstract [en]

    This paper presents a novel method for performing fast estimation of data samples on a desired output grid from samples on an irregularly sampled grid. The output signal is estimated using integration of signals over a neighbourhood employing a local model of the signal using discrete filters. The strength of the method is demonstrated in motion compensation examples by comparing to traditional techniques.

  • 3.
    Azizzadeh, Azad
    et al.
    Razi Univ, Iran.
    Mohammadkhani, Reza
    Univ Kurdistan, Iran.
    Makki, Seyed Vahab Al-Din
    Razi Univ, Iran.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    BER performance analysis of coarsely quantized uplink massive MIMO2019In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 161, p. 259-267Article in journal (Refereed)
    Abstract [en]

    Having lower quantization resolution, has been introduced in the literature, to reduce the power consumption of massive MIMO and millimeter wave MIMO systems. Here, we analyze the bit error rate (BER) performance of quantized uplink massive MIMO employing few-bit resolution ADCs. Considering ZF detection, we derive a signal-to-interference, quantization and noise ratio (SIQNR) to achieve an analytical BER approximation for coarsely quantized M-QAM massive MIMO systems, by using a linear quantization model. The proposed expression is a function of the quantization resolution in bits. We further numerically investigate the effects of different quantization levels, from 1-bit to 4-bits, on the BER of three modulation types QPSK, 16-QAM, and 64-QAM. The uniform and non-uniform quantizers are employed in our simulation. Monte Carlo simulation results reveal that our approximate formula gives a tight upper bound on the BER performance of b-bit resolution quantized systems using non-uniform quantizers, whereas the use of uniform quantizers cause a lower performance. We also found a small BER performance degradation in coarsely quantized systems, for example 2-3 bits QPSK and 3-4 bits 16-QAM, compared to the full-precision (unquantized) case. However, this performance degradation can be compensated by increasing the number of antennas at the BS. (C) 2019 Published by Elsevier B.V.

  • 4.
    Burak Guldogan, Mehmet
    et al.
    Linköping University, Department of Electrical Engineering. Linköping University, The Institute of Technology.
    Arikan, Orhan
    Bilkent University.
    Multipath channel identification by using global optimization in ambiguity function domain2011In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 91, no 11, p. 2647-2660Article in journal (Refereed)
    Abstract [en]

    A new transform domain array signal processing technique is proposed for identification of multipath communication channels. The received array element outputs are transformed to delay-Doppler domain by using the cross-ambiguity function (CAF) for efficient exploitation of the delay-Doppler diversity of the multipath components. Clusters of multipath components can be identified by using a simple amplitude thresholding in the delay-Doppler domain. Particle swarm optimization (PSO) can be used to identify parameters of the multipath components in each cluster. The performance of the proposed PSO-CAF technique is compared with the space alternating generalized expectation maximization (SAGE) technique and with a recently proposed PSO based technique at various SNR levels. Simulation results clearly quantify the superior performance of the PSO-CAF technique over the alternative techniques at all practically significant SNR levels.

  • 5.
    Eghbali, Amir
    et al.
    Linköping University, Department of Electrical Engineering, Electronics System. Linköping University, The Institute of Technology.
    Johansson, Håkan
    Linköping University, Department of Electrical Engineering, Electronics System. Linköping University, The Institute of Technology.
    A class of reconfigurable and low-complexity two-stage Nyquist filters2014In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 96, p. 164-172Article in journal (Refereed)
    Abstract [en]

    This paper introduces a class of reconfigurable two-stage Nyquist filters where the Farrow structure realizes the polyphase components of linear-phase finite-length impulse response (FIR) filters. By adjusting the variable predetermined multipliers of the Farrow structure, various linear-phase FIR Nyquist filters and integer interpolation/decimation structures are obtained, online. However, the filter design problem is solved only once, offline. Design examples, based on the reweighted l(1)-norm minimization, illustrate the proposed method. Savings in the arithmetic complexity are obtained when compared to the reconfigurable single-stage structures.

  • 6.
    Eghbali, Amir
    et al.
    Linköping University, Department of Electrical Engineering, Electronics System. Linköping University, The Institute of Technology.
    Johansson, Håkan
    Linköping University, Department of Electrical Engineering, Electronics System. Linköping University, The Institute of Technology.
    Saramaki, Tapio
    Tampere University of Technology, Finland .
    A method for the design of Farrow-structure based variable fractional-delay FIR filters2013In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 93, no 5, p. 1341-1348Article in journal (Refereed)
    Abstract [en]

    This paper proposes a method to design variable fractional-delay (FD) filters using the Farrow structure. In the transfer function of the Farrow structure, different subfilters are weighted by different powers of the FD value. As both the FD value and its powers are smaller than 0.5, our proposed method uses them as diminishing weighting functions. The approximation error, for each subfilter, is then increased in proportion to the power of the FD value. This gives a new distribution for the orders of the Farrow subfilters which has not been utilized before. This paper also includes these diminishing weighting functions in the filter design so as to obtain their optimal values, iteratively. We consider subfilters of both even and odd orders. Examples illustrate our proposed method and comparisons, to various earlier designs, show a reduction of the arithmetic complexity.

  • 7.
    Eghbali, Amir
    et al.
    Linköping University, Department of Electrical Engineering, Electronics System. Linköping University, The Institute of Technology.
    Saramaki, Tapio
    Tampere University of Technology, Finland .
    Johansson, Håkan
    Linköping University, Department of Electrical Engineering, Electronics System. Linköping University, The Institute of Technology.
    Conditions for Lth-band filters of order 2N as cascades of identical linear-phase FIR spectral factors of order N2014In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 97, no AprilArticle in journal (Refereed)
    Abstract [en]

    This paper presents formulas for the number of optimization parameters (degrees of freedom) when designing Type I linear-phase finite-length impulse response (FIR) Lth-band filters of order 2N as cascades of identical linear-phase FIR spectral factors of order N. We deal with two types of degrees of freedom referred to as (i) the total degrees of freedom D-T, and (ii) the remaining degrees of freedom D-R. Due to the symmetries or antisymmetries in the impulse responses of the spectral factors, D-T roughly equals N/2. Some of these parameters are specifically needed to meet the Lth-band conditions because, in an Lth-band filter, every Lth coefficient is zero and the center tap equals 1/L. The remaining D-R parameters can then be used to improve the stopband characteristics of the overall Lth-band filter. We derive general formulas for D-R with given pairs of L and N. It is shown that for a fixed L, the choices of N, in a close neighborhood, may even decrease D-R despite increasing the arithmetic complexity, order, and the delay.

  • 8. Elias, Elizabeth
    et al.
    Löwenborg, Per
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Electronics System.
    Johansson, Håkan
    Linköping University, Department of Electrical Engineering.
    Wanhammar, Lars
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering, Electronics System.
    Tree-structured IIR/FIR uniform-band and octave-band filter banks with very low-complexity analysis or synthesis filters2003In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 83, no 9, p. 1997-2009Article in journal (Refereed)
    Abstract [en]

    This paper introduces new tree-structured uniform-band and octave-band digital filter banks (FBs). These FBs make use of half-band IIR filters in the analysis FBs and FIR filters in the synthesis FBs. The resulting FBs are asymmetric in the sense that the analysis FB has a very low arithmetic complexity whereas that in the synthesis FB is higher. However, compared with other asymmetric FBs, the proposed ones have in many cases a lower overall arithmetic complexity and delay. The proposed FBs have magnitude distortion but no phase distortion, further, the aliasing components are either zero (uniform-band case) or approximately zero (octave-band case). The FBs are designed using linear and nonlinear programming. Design examples are included demonstrating the properties of the proposed filters banks. ⌐ 2003 Published by Elsevier B.V.

  • 9.
    Erdogmus, Deniz
    et al.
    Department of Electrical and Computer Eng., University of Florida, Gainesville, FL, USA.
    Larsson, Erik G.
    Department of Electrical and Computer Eng., University of Florida, Gainesville, FL, USA.
    Yan, Rui
    Department of Electrical and Computer Eng., University of Florida, Gainesville, FL, USA.
    Principe, Jose C.
    Department of Electrical and Computer Eng., University of Florida, Gainesville, FL, USA.
    Fitzimmons, Jeffrey R.
    Department of Radiology, University of Florida, Gainesville, FL, USA.
    Measuring the signal-to-noise ratio in magnetic resonance imaging: a caveat2004In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 84, no 6, p. 1035-1040Article in journal (Refereed)
    Abstract [en]

    The validity of the signal-to-noise ratio (SNR) as an objective quality measure for biomedical images has been the subject of a long-standing debate. Nevertheless, the SNR is the most popularly used measure both for assessing the quality of images and for evaluating the effectiveness of image enhancement and signal processing techniques. In this correspondence, we illustrate that under certain conditions the SNR can be changed by a nonlinear transformation, and also that it is often hard to measure objectively. Therefore, the issue is not only how well the SNR correlates with image quality as perceived by a human observer (which has been the primary subject of earlier debate), but also that SNR is questionable from a quantitative measurement point of view.

  • 10.
    Erdogmus, Deniz
    et al.
    Computational NeuroEngineering Laboratory, Department of Electrical & Computer Engineering, University of Florida, US.
    Larsson, Erik G.
    Department of Electrical & Computer Engineering, The George Washington University, USA.
    Yan, Rui
    Computational NeuroEngineering Laboratory, Department of Electrical & Computer Engineering, University of Florida, US.
    Principe, Jose C.
    Computational NeuroEngineering Laboratory, Department of Electrical & Computer Engineering, University of Florida, US.
    Fitzsimmons, Jeffrey R.
    Department of Radiology, University of Florida, USA.
    Asymptotic SNR-performance of some image combination techniques for phased-array MRI2004In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 84, no 6, p. 997-1003Article in journal (Refereed)
    Abstract [en]

    Phased-array magnetic resonance imaging technology is currently flourishing with the promise of obtaining a profitable trade-off between image quality and image acquisition speed. The image quality is generally measured in terms of the signal-to-noise ratio (SNR), which is often calculated using samples taken from the reconstructed image. In this paper, we derive analytical expressions for the asymptotic SNR in the final image for three different phased-array image combination methods, namely: (1) sum-of-squares, (2) singular value decomposition, and (3) normalized coil averaging. The SNR expressions are expressed in terms of the statistics of the noise in the measurements, as well as the coil sensitivity coefficients. Our results can facilitate a better understanding for the phased-array image combination problem, as well as provide a tool for the optimal design of coils.

  • 11.
    Granlund, Gösta
    Linköping University, Department of Electrical Engineering, Computer Vision . Linköping University, The Institute of Technology.
    The Complexity of Vision1999In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 74, no 1, p. 101-126Article in journal (Refereed)
    Abstract [en]

    There is no indication that it will ever be possible to find some simple trick that miraculously solves most problems in vision. It turns out that the processing system must be able to implement a model structure, the complexity of which is directly related to the structural complexity of the problem under consideration in the external world. It has become increasingly apparent that Vision cannot be treated in isolation from the response generation, because a very high degree of integration is required between different levels of percepts and corresponding response primitives. The response to be produced at a given instance is as much dependent upon the state of the system, as the percepts impinging upon the system. In addition, it has become apparent that many classical aspects of perception, such as geometry, probably do not belong to the percept domain of a Vision system, but to the response domain. This article will focus on what are considered crucial problems in Vision for robotics for the future, rather than on the classical solutions today. It will discuss hierarchical architectures for combination of percept and response primitives. It will discuss the concept of combined percept-response invariances as important structural elements for Vision. It will be maintained that learning is essential to obtain the necessary flexibility and adaptivity. In consequence, it will be argued that invariances for the purpose of Vision are not abstractly geometrical, but derived from the percept-response interaction with the environment. The issue of information representation becomes extremely important in distributed structures of the types foreseen, where uncertainty of information has to be stated for update of models and associated data. The question of object representation is central to the paper. Equivalence is established between the representations of response, geometry and time. Finally an integrated percept-response structure is proposed for flexible response control.

  • 12.
    Isaksson, Alf
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Millnert, Mille
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Inverse Glottal Filtering using a Parameterized Input Model1989In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 18, no 4, p. 435-445Article in journal (Refereed)
    Abstract [en]

    In this paper computational algorithms for inverse glottal filtering are studied. The objective of inverse glottal filtering is to estimate the driving source. A good model for the glottal pulse is useful for, e.g., speech synthesis, speech recognition and speaker diagnostics. One common approach is to use a parameterized model of the input signal, i.e., the glottal pulses. The algorithm presented enables simultaneous estimation of the parameters of the input signal and the parameters of the system transfer function, the vocal tract model. The presentation here is restricted to transfer functions of all-pole type, i.e., AR-models. The method can be extended to handle zeros in the transfer function. The computational burden would, however, increase significantly. The algorithm uses efficient numerical methods, as, for instance, QR-factorization through Householder transformations.

  • 13.
    Koski, Timo
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Mathematics, Mathematical Statistics .
    Hurd, H.
    The Wold isomorphism for cyclostationary sequences2004In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 84, no 5, p. 813-824Article in journal (Refereed)
    Abstract [en]

    In 1948 Wold introduced an isometric isomorphism between a Hilbert (linear) space formed from the weighted shifts of a numerical sequence and a suitable Hilbert space of values of a second-order stochastic sequence. Motivated by a recent resurrection of the idea in the context of cyclostationary sequences and processes, we present the details of the Wold isomorphism between cyclostationary stochastic sequences and cyclostationary numerical sequences. We show how Hilbert-space representations of cyclostationary sequences are interpreted in the case of numerical CS sequences.

  • 14.
    Larsson, Erik G.
    et al.
    Department of Electrical and Computer Engineering, University of Florida, USA.
    Stoica, Petre
    Department of Systems and Control, Uppsala University, Sweden.
    Li, Jian
    Department of Electrical and Computer Engineering, University of Florida, USA.
    Spectral estimation via adaptive filterbank methods: a unified analysis and a new algorithm2002In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 82, no 12, p. 1991-2001Article in journal (Refereed)
    Abstract [en]

    The problem of estimating the amplitude spectrum of a signal is of interest in a number of applications ranging from radar imaging to time-series analysis. The so-called adaptive filterbank-based nonparametric spectral estimators have recently received renewed interest as potential solutions to this problem. In essence, the adaptive filterbank methods determine an estimate of the spectrum for a frequency of interest by computing a finite impulse response filter according to a certain criterion and fitting a sinusoid to the filtered data sequence. In this paper, we first analyze the asymptotic estimation accuracy of the amplitude spectrum for various filterbank estimators. Next, we propose a new adaptive filterbank estimator based on a minimum mean square error criterion. Numerical examples indicate that the new estimator can have a better resolution capability than previously known filterbank estimators.

  • 15.
    Lindgren, David
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Hendeby, Gustaf
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Gustafsson, Fredrik
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Distributed localization using acoustic Doppler2015In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 107, p. 43-53Article in journal (Refereed)
    Abstract [en]

     It is well-known that the motion of an acoustic source can be estimated from Doppler shift observations. It is however not obvious how to design a sensor network to efficiently deliver the localization service. In this work a rather simplistic motion model is proposed that is aimed at sensor networks with realistic numbersof sensor nodes. It is also described how to efficiently solve the associated least squares optimization problem by Gauss-Newton variable projection techniques, and how to initiate the numerical search from simple features extracted from the observed frequency series. The methods are evaluated by Monte Carlo simulations and demonstrated on real data by localizing an all-terrain vehicle. Itis concluded that the processing components included are fairly mature for practical implementations in sensor networks.

  • 16.
    Lindgren, David
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Savas, Berkant
    Linköping University, Department of Mathematics, Scientific Computing. Linköping University, The Institute of Technology.
    Rank Reduction and Volume Minimization Approach to State-Space Subspace System Identification2006In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 86, no 11, p. 3275-3285Article in journal (Refereed)
    Abstract [en]

    In this paper we consider the reduced rank regression problem

    solved by maximum-likelihood-inspired state-space subspace system identification algorithms. We conclude that the determinant criterion is, due to potential rank-deficiencies, not general enough to handle all problem instances. The main part of the paper analyzes the structure of the reduced rank minimization problem and identifies signal properties in terms of geometrical concepts. A more general minimization criterion is considered, rank reduction followed by volume minimization. A numerically sound algorithm for minimizing this criterion is presented and validated on both simulated and experimental data.

  • 17.
    Ljung, Lennart
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Aspects on the System Identification Problem1982In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 4, no 5-6, p. 445-456Article in journal (Refereed)
    Abstract [en]

    System Identification concerns the problem of building mathematical models of a dynamical system from measured input-output data. In this paper we examine some aspects of this problem. Typical sets of models are displayed and basic principles for fitting them to data are discussed. Asymptotic properties of the resulting model are also quoted.

  • 18.
    Ljung, Lennart
    et al.
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    McKelvey, Tomas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Subspace Identification from Closed Loop Data1996In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 52, no 2, p. 209-215Article in journal (Refereed)
    Abstract [en]

    The so-called subspace methods for direct identification of linear models in state space form have drawn considerable interest recently. They have been found to work well in many cases but have one drawback — they do not yield consistent estimates for data collected under output feedback. The present paper points to the reasons for this. We stress how the basic idea is to focus on the estimation of the state-variable candidates — the k-step ahead output predictors. By recomputing these from a ‘non-parametric’ (or, rather, high order ARX) one-step ahead predictor model, closed loop data can be handled.

  • 19.
    Savic, Vladimir
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Wymeersch, Henk
    Chalmers University of Technology, Gothenburg, Sweden.
    Zazo, Santiago
    Technical University of Madrid, Spain.
    Belief consensus algorithms for fast distributed target tracking in wireless sensor networks2014In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 95, p. 149-160Article in journal (Refereed)
    Abstract [en]

    In distributed target tracking for wireless sensor networks, agreement on the target state can be achieved by the construction and maintenance of a communication path, in order to exchange information regarding local likelihood functions. Such an approach lacks robustness to failures and is not easily applicable to ad-hoc networks. To address this, several methods have been proposed that allow agreement on the global likelihood through fully distributed belief consensus (BC) algorithms, operating on local likelihoods in distributed particle filtering (DPF). However, a unified comparison of the convergence speed and communication cost has not been performed. In this paper, we provide such a comparison and propose a novel BC algorithm based on belief propagation (BP). According to our study, DPF based on metropolis belief consensus (MBC) is the fastest in loopy graphs, while DPF based on BP consensus is the fastest in tree graphs. Moreover, we found that BC-based DPF methods have lower communication overhead than data flooding when the network is sufficiently sparse.

  • 20.
    Tran Viet, Linh
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Science and Technology.
    Lenz, Reiner
    Linköping University, Department of Science and Technology, Digital Media. Linköping University, The Institute of Technology.
    Compact colour descriptors for colour-based image retrieval2005In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 85, no 2, p. 233-246Article in journal (Refereed)
    Abstract [en]

    In many colour-based image retrieval systems the colour properties of an image are described by its colour histogram. Histogram-based search is, however, often inefficient for large histogram sizes. Therefore we introduce several new, Karhunen-Loève transform (KLT)-based methods that provide efficient representations of colour histograms and differences between two colour histograms. The methods are based on the following two observations, Ordinary KLT considers colour histograms as signals and uses the Euclidian distance for optimization, KLT with generalized colour distance measures that take into account both the statistical properties of the image database and the properties of the underlying colour space should improve the retrieval performance. Image retrieval applications compare similarities between different images. Relevant for the decision is only the local structure of the image space around the current query image since the task is to find those images in the database that are most similar to this given query image. Therefore only the local topology of the feature space is of interest and compression methods should preserve this local topology as much as possible. It is therefore more important to have a good representation of the differences between features of similar images than good representations of the features of the images themselves. The optimization should therefore be based on minimizing the approximation error in the space of local histogram differences instead of the space of colour histograms. In this paper we report the results of our experiments that are done on three image databases containing more than 130,000 images. Both objective and subjective ground truth queries are used in order to evaluate the proposed methods and to compare them with other existing methods. The results from our experiments show that compression methods based on a combination of the two observations described above provide new, powerful and efficient retrieval algorithms for colour-based image retrieval. © 2004 Elsevier B.V. All rights reserved.

  • 21.
    Viberg, Mats
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
    Sensitivity of Parametric Direction Finding to Colored Noise Fields and Undermodeling1993In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 34, no 2, p. 207-222Article in journal (Refereed)
    Abstract [en]

    A fundamental assumption for most direction finding algorithms is that the spatial correlation structure of the background noise (i.e., the correlation from sensor to sensor) is known to within a multiplicative scalar. In practive, this is often achieved by measuring the array covariance when no signals are present, a procedure which is unavoidably subjected to errors. The presence of undetected weak signals gives rise to similar perturbations. In this paper, the effect of such modeling errors on parametric estimation techniques is examined. First-order expressions for the mean square error (MSE) of the parameter estimates are derived for the deterministic and stochastic maximum likelihood methods and the weighted subspace fitting technique. The spatial noise correlation structures that lead to maximum performance loss are identified under different assumptions. In case of high signal-to-noise ratio, it is found that the MSE can be increased by a factor equal to the number of sensors in the array, as compared to spatially white noise. Furthermore, it is demonstrated that the presence of a relatively weak (− 15 dB) undetected signal can result in a large bias (≈1°) on the estimates of the other signal directions.

  • 22.
    Wang, Gaihua
    et al.
    School of Electrical and Electronic Engineering, Hubei University of Technology, China.
    Liu, Yang
    School of Electrical and Electronic Engineering, Hubei University of Technology, China / Faculty of Technology, University of Vaasa, Vaasa, Finland.
    Zhao, Tongzhou
    Hubei Province Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, China.
    A quaternion-based switching filter for colour image denoising2014In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 102, p. 216-225Article in journal (Refereed)
    Abstract [en]

    An improved quaternion switching filter for colour image denoising is presented. It proposes a RGB colour image as a pure quaternion form and measures differences between two colour pixels with the quaternion-based distance. Further, in noise-detection, a two-stage detection method is proposed to determine whether the current pixel is noise or not. The noisy pixels are replaced by the vector median filter (VMF) output and the noise-free ones are unchanged. Finally, we combine the advantages of quaternion-based switching filter and non-local means filter to remove mixture noise. By comparing the performance and computing time processing different images, the proposed method has superior performance which not only provides the best noise suppression results but also yields better image quality compared to other widely used filters.

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  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf