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Showing papers in "IEEE Signal Processing Letters in 2002"


Journal ArticleDOI
TL;DR: Although the new index is mathematically defined and no human visual system model is explicitly employed, experiments on various image distortion types indicate that it performs significantly better than the widely used distortion metric mean squared error.
Abstract: We propose a new universal objective image quality index, which is easy to calculate and applicable to various image processing applications. Instead of using traditional error summation methods, the proposed index is designed by modeling any image distortion as a combination of three factors: loss of correlation, luminance distortion, and contrast distortion. Although the new index is mathematically defined and no human visual system model is explicitly employed, our experiments on various image distortion types indicate that it performs significantly better than the widely used distortion metric mean squared error. Demonstrative images and an efficient MATLAB implementation of the algorithm are available online at http://anchovy.ece.utexas.edu//spl sim/zwang/research/quality_index/demo.html.

5,285 citations


Journal ArticleDOI
TL;DR: A new impulse noise detection technique for switching median filters is presented, which is based on the minimum absolute value of four convolutions obtained using one-dimensional Laplacian operators, and is directed toward improved line preservation.
Abstract: A new impulse noise detection technique for switching median filters is presented, which is based on the minimum absolute value of four convolutions obtained using one-dimensional Laplacian operators. Extensive simulations show that the proposed filter provides better performance than many of the existing switching median filters with comparable computational complexity. In particular, the proposed filter is directed toward improved line preservation.

688 citations


Journal ArticleDOI
TL;DR: A minima controlled recursive averaging (MCRA) approach for noise estimation that is computationally efficient, robust with respect to the input signal-to-noise ratio (SNR) and type of underlying additive noise, and characterized by the ability to quickly follow abrupt changes in the noise spectrum.
Abstract: In this letter, we introduce a minima controlled recursive averaging (MCRA) approach for noise estimation. The noise estimate is given by averaging past spectral power values and using a smoothing parameter that is adjusted by the signal presence probability in subbands. The presence of speech in subbands is determined by the ratio between the local energy of the noisy speech and its minimum within a specified time window. The noise estimate is computationally efficient, robust with respect to the input signal-to-noise ratio (SNR) and type of underlying additive noise, and characterized by the ability to quickly follow abrupt changes in the noise spectrum.

644 citations


Journal ArticleDOI
TL;DR: This letter presents a locally adaptive denoising algorithm using the bivariate shrinkage function and is illustrated using both the orthogonal and dual tree complex wavelet transforms.
Abstract: The performance of image-denoising algorithms using wavelet transforms can be improved significantly by taking into account the statistical dependencies among wavelet coefficients as demonstrated by several algorithms presented in the literature. In two earlier papers by the authors, a simple bivariate shrinkage rule is described using a coefficient and its parent. The performance can also be improved using simple models by estimating model parameters in a local neighborhood. This letter presents a locally adaptive denoising algorithm using the bivariate shrinkage function. The algorithm is illustrated using both the orthogonal and dual tree complex wavelet transforms. Some comparisons with the best available results are given in order to illustrate the effectiveness of the proposed algorithm.

617 citations


Journal ArticleDOI
TL;DR: Through adopting a polynomial kernel, the principal components can be computed within the space spanned by high-order correlations of input pixels making up a facial image, thereby producing a good performance.
Abstract: A kernel principal component analysis (PCA) was previously proposed as a nonlinear extension of a PCA. The basic idea is to first map the input space into a feature space via nonlinear mapping and then compute the principal components in that feature space. This article adopts the kernel PCA as a mechanism for extracting facial features. Through adopting a polynomial kernel, the principal components can be computed within the space spanned by high-order correlations of input pixels making up a facial image, thereby producing a good performance.

520 citations


Journal ArticleDOI
TL;DR: An adaptive procedure for signal representation is proposed, which improves upon the earlier proposed matching pursuit and orthogonal matching pursuit approaches.
Abstract: An adaptive procedure for signal representation is proposed. The representation is built up through functions (atoms) selected from a redundant family (dictionary). At each iteration, the algorithm gives rise to an approximation of a given signal, which is guaranteed (1) to be the orthogonal projection of a signal onto the subspace generated by the selected atoms and (2) to minimize the norm of the corresponding residual error. The approach is termed optimized orthogonal matching pursuit because it improves upon the earlier proposed matching pursuit and orthogonal matching pursuit approaches.

309 citations


Journal ArticleDOI
TL;DR: An optimally modified log-spectral amplitude estimator is presented, which minimizes the mean-square error of the log-Spectra for speech signals under signal presence uncertainty and introduces an efficient estimator for the a priori speech absence probability.
Abstract: We present an optimally modified log-spectral amplitude estimator, which minimizes the mean-square error of the log-spectra for speech signals under signal presence uncertainty. We propose an estimator for the a priori signal-to-noise ratio (SNR), and introduce an efficient estimator for the a priori speech absence probability. Speech presence probability is estimated for each frequency bin and each frame by a soft-decision approach, which exploits the strong correlation of speech presence in neighboring frequency bins of consecutive frames. Objective and subjective evaluation confirm superiority in noise suppression and quality of the enhanced speech.

251 citations


Journal ArticleDOI
TL;DR: In this paper, a bilinear mapping operator referred to as the cubic phase (CP) function is introduced, where the energy of the CP function is concentrated along the frequency rate law of the signal.
Abstract: This letter introduces a two-dimensional bilinear mapping operator referred to as the cubic phase (CP) function. For first-, second-, or third-order polynomial phase signals, the energy of the CP function is concentrated along the frequency rate law of the signal. The function, thus, has an interpretation as a time-frequency rate representation. The peaks of the CP function yield unbiased estimates of the instantaneous (angular) frequency rate (IFR) and, hence, can be used as the basis for an IFR estimation algorithm. The letter defines an IFR estimation algorithm and theoretically analyzes it. The estimation is seen to be asymptotically optimal at the center of the data record for high signal-to-noise ratios. Simulations are provided to verify the theoretical claims.

179 citations


Journal ArticleDOI
TL;DR: A method of combined source and channel coding is described that provides robustness to errors from a binary symmetric channel and uses the JPEG2000 (JP2) image compression standard.
Abstract: A method of combined source and channel coding is described that provides robustness to errors from a binary symmetric channel and uses the JPEG2000 (JP2) image compression standard. The source code rate and channel code rate are jointly optimized to produce a stream of fixed-size channel packets, such that the rate allocation complexity grows O(N/sup 2/) with the number of transmitted packets, N. Punctured turbo codes are used for channel coding, providing strong error protection. The rate allocation scheme presented obtains all necessary information from the JP2 encoder, and does not require image decompression.

165 citations


Journal ArticleDOI
TL;DR: This letter exploits the cyclic prefix to create a blind adaptive globally convergent channel-shortening algorithm, with a complexity like least mean squares, which is related to that of the shortening signal-to-noise solution of Melsa et al.
Abstract: This letter exploits the cyclic prefix to create a blind adaptive globally convergent channel-shortening algorithm, with a complexity like least mean squares. The cost function is related to that of the shortening signal-to-noise solution of Melsa et al. (see IEEE Trans. Commun., vol.44, p.1662-72, Dec. 1996), and simulations are provided to demonstrate the performance of the algorithm.

152 citations


Journal ArticleDOI
TL;DR: A method is presented that allows closed-form expressions for the correlation function to be obtained for arbitrary scattering distribution functions for general distributions of scatterers.
Abstract: The well-known results of the spatial correlation function for two-dimensional and three-dimensional diffuse fields of narrowband signals are generalized to the case of general distributions of scatterers. A method is presented that allows closed-form expressions for the correlation function to be obtained for arbitrary scattering distribution functions. These closed-form expressions are derived for a variety of commonly used scattering distribution functions.

Journal ArticleDOI
TL;DR: This work considers the noiseless linear independent component analysis problem, in the case where the hidden sources s are nonnegative, and shows that y is a permutation of the s if and only if y is nonnegative with probability 1.
Abstract: We consider the noiseless linear independent component analysis problem, in the case where the hidden sources s are nonnegative. We assume that the random variables si are well grounded in that they have a nonvanishing probability density function (PDF) in the (positive) neighborhood of zero. For an orthonormal rotation y=Wx of prewhitened observations x=QAs, under certain reasonable conditions we show that y is a permutation of the s (apart from a scaling factor) if and only if y is nonnegative with probability 1. We suggest that this may enable the construction of practical learning algorithms, particularly for sparse nonnegative sources.

Journal ArticleDOI
Biao Chen1
TL;DR: A maximum likelihood estimate for orthogonal frequency division multiplexing (OFDM) carrier frequency offset in the presence of virtual carriers is developed and it is found that the resulting estimate has an identical form to that of a previously proposed blind OFDM carriers frequency offset estimate.
Abstract: We develop a maximum likelihood estimate for orthogonal frequency division multiplexing (OFDM) carrier frequency offset in the presence of virtual carriers. It is found that the resulting estimate has an identical form to that of a previously proposed blind OFDM carrier frequency offset estimate by Liu and Tureli (see IEEE Commun. Lett., vol.2, p.104-106, 1998). Insights are provided as to why these two algorithms are equivalent.

Journal ArticleDOI
TL;DR: A short proof based on complementary subspaces of equivalence between a linearly constrained minimum-variance beamformer and generalized sidelobe canceller is presented.
Abstract: Charles Jim (1977) showed the conditions under which a linearly constrained minimum-variance (LCMV) beamformer produces outputs equivalent to a generalized sidelobe canceller (GSC). Buckley (1986) has stated that the proof of equivalence extends to general multilinear constraints. In this article a short proof based on complementary subspaces is presented.

Journal ArticleDOI
TL;DR: A new method to design prototype filters for conventional cosine-modulated pseudo-quadrature mirror filter (QMF) banks is presented, and the 3-dB cutoff frequency of the filter obtained at /spl pi//2M is set.
Abstract: We present a new method to design prototype filters for conventional cosine-modulated pseudo-quadrature mirror filter (QMF) banks. This method is based on windowing, and sets the 3-dB cutoff frequency of the filter obtained at /spl pi//2M. In this way, the filter bank performance can be significantly improved compared to other existing design methods.

Journal ArticleDOI
TL;DR: A bitplane-by-bitplane shift (BbBShift) method is proposed, which supports both arbitrary ROI shape and arbitrary scaling without shape coding.
Abstract: The JPEG2000 image coding standard defines two kinds of region of interest (ROI) coding methods-the general scaling based method and the maximum shift (maxshift) method. The former requires shape coding of the ROIs, which leads to increased complexity of codec implementations and limits the choice of ROI shapes (currently, only rectangle and ellipse shapes are defined). The latter allows for arbitrarily shaped ROI coding without explicitly transmitting any shape information to the decoder, but does not have the flexibility to select an arbitrary scaling value to define the relative importance of the ROI and the background wavelet coefficients. We propose a bitplane-by-bitplane shift (BbBShift) method, which supports both arbitrary ROI shape and arbitrary scaling without shape coding.

Journal ArticleDOI
TL;DR: A performance evaluation and comparison of G.729, AMR, and fuzzy voice activity detection (FVAD) algorithms was made using objective, psychoacoustic, and subjective parameters to evaluate the extent to which VADs depend on language, the signal-to-noise ratio, or the power level.
Abstract: The paper proposes a performance evaluation and comparison of G.729, AMR, and fuzzy voice activity detection (FVAD) algorithms. The comparison was made using objective, psychoacoustic, and subjective parameters. A highly varied speech database was also set up to evaluate the extent to which VADs depend on language, the signal-to-noise ratio (SNR), or the power level.

Journal ArticleDOI
TL;DR: A constant-modulus-algorithm-based multiuser detection scheme is proposed for a communication system under multipath propagation that integrates multiple constraints into the optimization criterion to mitigate channel distortion andMultiuser interference.
Abstract: In this letter, a constant-modulus-algorithm-based multiuser detection scheme is proposed for a communication system under multipath propagation. To mitigate channel distortion and multiuser interference, we integrate multiple constraints into the optimization criterion. According to our analysis, the ability of the detector to remove all interference is ensured in the absence of noise when the constraints are properly preselected. However, in the presence of noise, the constraints highly affect the performance of the receiver. In order to optimally combine signals from different paths to achieve performance gains, those constraints can also be treated as variables and jointly optimized with the receiver, as verified by numerical examples.

Journal ArticleDOI
TL;DR: In an active noise control (ANC) system using the filtered-x least mean square (FxLMS) algorithm, an online secondary path modeling method that uses an injected auxiliary noise is often applied, increasing the residual noise of the ANC system.
Abstract: In an active noise control (ANC) system using the filtered-x least mean square (FxLMS) algorithm, an online secondary path modeling method that uses an injected auxiliary noise is often applied Such a method allows quick and full-band signal-independent modeling In addition, it is suitable for multisecondary path modeling Normally, the larger the auxiliary noise, the faster an accurate model can be obtained However, it increases the residual noise of the ANC system To mitigate this problem, in this letter, a new online secondary path modeling method is proposed Rather than fixed, the power of auxiliary noise is varied according to the working status of the ANC system More specifically, the auxiliary noise is large before the ANC system converges, and becomes small when the system converges Computer simulations show its effectiveness and robustness

Journal ArticleDOI
TL;DR: A segment-based matching-pursuit algorithm where the psychoacoustical properties of the human auditory system are taken into account and a psychoacoustic-adaptive norm on the signal space is defined that can be used for assigning the dictionary elements to the individual segments in a rate-distortion optimal way.
Abstract: We propose a segment-based matching-pursuit algorithm where the psychoacoustical properties of the human auditory system are taken into account. Rather than scaling the dictionary elements according to auditory perception, we define a psychoacoustic-adaptive norm on the signal space that can be used for assigning the dictionary elements to the individual segments in a rate-distortion optimal way. The new algorithm is asymptotically equal to signal-to-mask-ratio-based algorithms in the limit of infinite-analysis window length. However, the new algorithm provides a significantly improved selection of the dictionary elements for finite window length.

Journal ArticleDOI
TL;DR: New improvements to range image segmentation based on edge detection techniques are presented, better preserves the object's topology and shape even to noisy images and does not depend on rigid threshold values, thus being useful in unsupervised systems.
Abstract: This article presents new improvements to range image segmentation based on edge detection techniques The developed approach better preserves the object's topology and shape even to noisy images The algorithm also does not depend on rigid threshold values, thus being useful in unsupervised systems Experiments were performed in a popular range image database and the results were compared to four other traditional range image segmentation algorithms, demonstrating the efficiency of the proposed algorithm

Journal ArticleDOI
TL;DR: A spatial filtering algorithm based on the estimation of the spatial signature vector of the interferer from shortterm spatial covariance matrices followed by a subspace projection to remove that dimension from the covariance matrix, and by further averaging.
Abstract: We investigate spatial filtering techniques for interference removal in multichannel radio astronomical observations. The techniques are based on the estimation of the spatial signature vector of the interferer from short-term spatial covariance matrices followed by a subspace projection to remove that dimension from the covariance matrix, and by further averaging. The projections will also modify the astronomical data, and hence a correction has to be applied to the long-term average to compensate for this. As shown by experimental results, the proposed technique leads to significantly improved estimates of the interference-free covariance matrix.

Journal ArticleDOI
TL;DR: The proposed method is based on a seamless integration of the two schemes without compromising their desirable features and makes feasible the deployment of the merits of a BPCS steganography technique in a practical scenario where images are compressed before being transmitted over the network.
Abstract: This letter presents a steganography method based on a JPEG2000 lossy compression scheme and bit-plane complexity segmentation (BPCS) steganography. It overcomes the lack of robustness of bit-plane-based steganography methods with respect to lossy compression of a dummy image: a critical shortcoming that has hampered deployment in a practical scenario. The proposed method is based on a seamless integration of the two schemes without compromising their desirable features and makes feasible the deployment of the merits of a BPCS steganography technique in a practical scenario where images are compressed before being transmitted over the network. Embedding rates of around 15% of the compressed image size were achieved for preembedding 1.0-bpp compressed images with no noticeable degradation in image quality.

Journal ArticleDOI
TL;DR: A new subspace approach is proposed for enhancement of speech corrupted by colored noise based on the simultaneous diagonalization of the clean speech and noise covariance matrices, which leads to an optimal linear estimator that minimizes speech distortion subject to the noise distortion being below a set threshold.
Abstract: A new subspace approach is proposed for enhancement of speech corrupted by colored noise. The proposed approach is based on the simultaneous diagonalization of the clean speech and noise covariance matrices, which leads to an optimal linear estimator that minimizes speech distortion subject to the noise distortion being below a set threshold. The proposed approach is shown to be a generalization of the approach proposed by Ephraim and Van Trees (1995) for white noise. Objective and subjective measures demonstrated significant improvements over other subspace-based methods when tested with sentences corrupted with speech-shaped noise and multitalker babble.

Journal ArticleDOI
TL;DR: It is shown that the centroid induced by the symmetrical Kullback-Leibler distance is the unique zeroing argument of a function which only depends on the arithmetic and the normalized geometric mean of the cluster.
Abstract: This paper discusses the computation of the centroid induced by the symmetrical Kullback-Leibler distance. It is shown that it is the unique zeroing argument of a function which only depends on the arithmetic and the normalized geometric mean of the cluster. An efficient algorithm for its computation is presented. Speech spectra are used as an example.

Journal ArticleDOI
TL;DR: An online preprocessing technique is proposed, which, although very simple, is able to provide significant improvements in the compression ratio of the images that it targets and shows a good robustness on other images.
Abstract: This article addresses the problem of improving the efficiency of lossless compression of images with sparse histograms. An online preprocessing technique is proposed, which, although very simple, is able to provide significant improvements in the compression ratio of the images that it targets and shows a good robustness on other images.

Journal ArticleDOI
TL;DR: A new robust interpolation approach is developed by minimizing the interpolation error inside the sectors of interest while setting multiple "stopband" constraints outside these sectors to prevent performance degradation effects caused by out-of-sector sources.
Abstract: We study Friedlander's (1993) array interpolation technique, whose main shortcoming in multisource scenarios is that it does not provide sufficient robustness against sources arriving outside specified interpolation sectors. In this letter, we develop a new robust interpolation approach by minimizing the interpolation error inside the sectors of interest while setting multiple "stopband" constraints outside these sectors to prevent performance degradation effects caused by out-of-sector sources. Computationally efficient convex formulations of the robust interpolation matrix design problem using second-order cone programming are derived.

Journal ArticleDOI
TL;DR: This letter describes an algorithm for systematically finding a multiplierless approximation of transforms by replacing floating-point multipliers with VLSI-friendly binary coefficients of the form k/2/sup n/.
Abstract: This letter describes an algorithm for systematically finding a multiplierless approximation of transforms by replacing floating-point multipliers with VLSI-friendly binary coefficients of the form k/2/sup n/. Assuming the cost of hardware binary shifters is negligible, the total number of binary adders employed to approximate the transform can be regarded as an index of complexity. Because the new algorithm is more systematic and faster than trial-and-error binary approximations with adder constraint, it is a much more efficient design tool. Furthermore, the algorithm is not limited to a specific transform; various approximations of the discrete cosine transform are presented as examples of its versatility.

Journal ArticleDOI
TL;DR: This letter treats a class of adaptive update-lifting schemes that do not require bookkeeping for perfect reconstruction that are triggered by a binary threshold criterion based on a generalized gradient chosen so that it ignores portions of a signal that are polynomial up to a given order.
Abstract: This letter treats a class of adaptive update-lifting schemes that do not require bookkeeping for perfect reconstruction. The choice of the update-lifting filter is triggered by a binary threshold criterion based on a generalized gradient that is chosen in such a way that it only smooths homogeneous regions. This criterion can be chosen so that it ignores portions of a signal that are polynomial up to a given order. The update-lifting filter modifies the signal in these polynomial regions but leaves other portions unaffected.

Journal ArticleDOI
TL;DR: If the global component of the transform domain LMS is also made time-variable, depending on the output error, the speed of convergence can be significantly improved.
Abstract: We introduce a new transform domain (least mean square) LMS algorithm with variable step. The existing approaches use different time-variable step-sizes for each filter tap. The step-sizes are time-variable due to the power estimates of each transform coefficient. In our new approach, for each step-size we define a local component that is given by the power normalization, and a global component that is the same for each filter coefficient. We show that if the global component is also made time-variable, depending on the output error, the speed of convergence can be significantly improved.