Showing papers on "Noise reduction published in 1998"

A general theory of phase noise in electrical oscillators

Abstract: A general model is introduced which is capable of making accurate, quantitative predictions about the phase noise of different types of electrical oscillators by acknowledging the true periodically time-varying nature of all oscillators. This new approach also elucidates several previously unknown design criteria for reducing close-in phase noise by identifying the mechanisms by which intrinsic device noise and external noise sources contribute to the total phase noise. In particular, it explains the details of how 1/f noise in a device upconverts into close-in phase noise and identifies methods to suppress this upconversion. The theory also naturally accommodates cyclostationary noise sources, leading to additional important design insights. The model reduces to previously available phase noise models as special cases. Excellent agreement among theory, simulations, and measurements is observed.

Nonlinear wavelet image processing: variational problems, compression, and noise removal through wavelet shrinkage

Abstract: This paper examines the relationship between wavelet-based image processing algorithms and variational problems. Algorithms are derived as exact or approximate minimizers of variational problems; in particular, we show that wavelet shrinkage can be considered the exact minimizer of the following problem. Given an image F defined on a square I, minimize over all g in the Besov space B11(L1(I)) the functional |F-g|L2(I)2+λ|g|(B11(L1(I))). We use the theory of nonlinear wavelet image compression in L2(I) to derive accurate error bounds for noise removal through wavelet shrinkage applied to images corrupted with i.i.d., mean zero, Gaussian noise. A new signal-to-noise ratio (SNR), which we claim more accurately reflects the visual perception of noise in images, arises in this derivation. We present extensive computations that support the hypothesis that near-optimal shrinkage parameters can be derived if one knows (or can estimate) only two parameters about an image F: the largest α for which F∈Bqα(Lq(I)),1/q=α/2+1/2, and the norm |F|Bqα(Lq(I)). Both theoretical and experimental results indicate that our choice of shrinkage parameters yields uniformly better results than Donoho and Johnstone's VisuShrink procedure; an example suggests, however, that Donoho and Johnstone's (1994, 1995, 1996) SureShrink method, which uses a different shrinkage parameter for each dyadic level, achieves a lower error than our procedure.

A new technique for noise filtering of SAR interferometric phase images

Abstract: This paper addresses the noise filtering problem for synthetic aperture radar (SAR) interferometric phase images. The phase noise is characterized by an additive noise model. The model is verified with an L-band shuttle imaging radar (SIR)-C interferogram. An adaptive filtering algorithm based on this noise model is developed. It emphasizes filtering noise adaptively according to the local noise level and filtering along fringes using directionally dependent windows. This algorithm is effective, especially for the tightly packed fringes of X-band interferometry. Using simulated and SIR-C/X-SAR repeat-pass generated interferograms, the effectiveness of this filter is demonstrated by its capabilities in residue reduction, adaptive noise filtering, and its ability to filter areas with high fringe rates. In addition, a scheme of incorporating this filtering algorithm in iterative phase unwrapping using a least-squares method is proposed.

Analysis of noise reduction and dereverberation techniques based on microphone arrays with postfiltering

Abstract: In teleconferencing systems, the use of hands-free sound pick-up reduces speech quality. This is due to ambient noise, acoustic echo, and the reverberation produced by the acoustical environment. This paper sets out to present a theoretical analysis of noise reduction and dereverberation algorithms based on a microphone array combined with a Wiener postfilter. It is shown that the transfer function of the postfilter depends on the input signal-to-noise ratio (SNR) and on the noise reduction yielded by the array. The use of a directivity-controlled array instead of a conventional beam-former is proposed to improve the performance of the whole system. Examples in real room environments are provided, which confirm the theoretical results, It is observed that the postfilter gives a limited reduction of the reverberation. On the contrary, an appreciable reduction of acoustic echo and localized noise is obtained and makes the whole system highly attractive for hands-free communication systems.

Wavelet decomposition approaches to statistical inverse problems

Abstract: SUMMARY A wide variety of scientific settings involve indirect noisy measurements where one faces a linear inverse problem in the presence of noise. Primary interest is in some function f(t) but data are accessible only about some linear transform corrupted by noise. The usual linear methods for such inverse problems do not perform satisfactorily when f(t) is spatially inhomogeneous. One existing nonlinear alternative is the wavelet-vaguelette decomposition method, based on the expansion of the unknown f(t) in wavelet series. In the vaguelette-wavelet decomposition method proposed here, the observed data are expanded directly in wavelet series. The performances of various methods are compared through exact risk calculations, in the context of the estimation of the derivative of a function observed subject to noise. A result is proved demonstrating that, with a suitable universal threshold somewhat larger than that used for standard denoising problems, both the wavelet-based approaches have an ideal spatial adaptivity property.

2-D companding for noise reduction in strain imaging

Abstract: Companding is a signal preprocessing technique for improving the precision of correlation-based time delay measurements. In strain imaging, companding is applied to warp 2-D or 3-D ultrasonic echo fields to improve coherence between data acquired before and after compression. It minimizes decorrelation errors, which are the dominant source of strain image noise. The word refers to a spatially variable signal scaling that compresses and expands waveforms acquired in an ultrasonic scan plane or volume. Temporal stretching by the applied strain is a single-scale (global), 1-D companding process that has been used successfully to reduce strain noise. This paper describes a two-scale (global and local), 2-D companding technique that is based on a sum-absolute-difference (SAD) algorithm for blood velocity estimation. Several experiments are presented that demonstrate improvements in target visibility for strain imaging. The results show that, if tissue motion can be confined to the scan plane of a linear array transducer, displacement variance can be reduced two orders of magnitude using 2-D local companding relative to temporal stretching.

A parametric formulation of the generalized spectral subtraction method

Abstract: In this paper, two short-time spectral amplitude estimators of the speech signal are derived based on a parametric formulation of the original generalized spectral subtraction method. The objective is to improve the noise suppression performance of the original method while maintaining its computational simplicity. The proposed parametric formulation describes the original method and several of its modifications. Based on the formulation, the speech spectral amplitude estimator is derived and optimized by minimizing the mean-square error (MSE) of the speech spectrum. With a constraint imposed on the parameters inherent in the formulation, a second estimator is also derived and optimized. The two estimators are different from those derived in most modified spectral subtraction methods, which are predominantly nonstatistical. When tested under stationary white Gaussian noise and semistationary Jeep noise, they showed improved noise suppression results.

Fetal ECG extraction with nonlinear state-space projections

Abstract: Describes a method to suppress maternal and noise contaminations in single-lead fetal ECG recordings. A nonlinear state space projection technique originally developed for noise reduction in deterministically chaotic signals is used. The method is successfully applied to recordings with fetal components and noise of comparable amplitude.

Modified LMS algorithms for speech processing with an adaptive noise canceller

Abstract: A desired signal corrupted by additive noise can often be recovered by an adaptive noise canceller using the least mean squares (LMS) algorithm. A major disadvantage of the LMS algorithm is its excess mean-squared error, or misadjustment, which increases linearly with the desired signal power, This leads to degrading performance when the desired signal exhibits large power fluctuations and is a serious problem in many speech processing applications. This work considers two modified LMS algorithms, the weighted sum and sum methods, designed to solve this problem by reducing the size of the steps in the weight update equation when the desired signal is strong. The weighted sum method is derived from an optimal method (also developed in this work), which is not generally applicable because it requires quantities unavailable in a practical system. The previously proposed, but ad hoc, sum method is analyzed and compared to the weighted sum method. Analysis of the two modified LMS algorithms indicates that either one provides substantial improvements in the presence of strong desired signals and similar performance in the presence of weak desired signals, relative to the unmodified LMS algorithm. Computer simulations with both uncorrelated Gaussian noise and speech signals confirm the results of the analysis and demonstrate the effectiveness of the modified algorithms. The modified LMS algorithms are particularly suited for signals (such as speech) that exhibit large fluctuations in short-time power levels.

Postprocessing method for suppressing musical noise generated by spectral subtraction

Abstract: We investigate whether musical noise, which often exists in speech enhanced using spectral subtraction, can be suppressed. Via exploiting some specific characteristics of human speech, we propose a method that can effectively suppress musical noise without a noticeable effect on speech intelligibility. Performance assessments confirm that our method is effective.

A novel psychoacoustically motivated audio enhancement algorithm preserving background noise characteristics

Abstract: In this paper we propose an algorithm for reduction of noise in audio signals. In contrast to several previous approaches we do not try to achieve a complete removal of the noise, but instead our goal is to preserve a pre-defined amount of the original noise in the processed signal. This is accomplished by exploiting the masking properties of the human auditory system. The speech and noise distortions are considered separately. The spectral weighting rule, adapted by utilizing only estimates of the masking threshold and the noise power spectral density, has been designed to guarantee complete masking of distortions of the residual noise. Simulation results confirm that no audible artifacts are left in the processed signal, while speech distortions are comparable to those caused by conventional noise reduction techniques.

A wavelet-based reduction of heart sound noise from lung sounds

Abstract: Heart sounds produce an incessant noise during lung sounds recordings. This noise severely contaminates the breath sounds signal and interferes in the analysis of lung sounds. In this paper, the use of a wavelet transform domain filtering technique as an adaptive de-noising tool, implemented in lung sounds analysis, is presented. The multiresolution representations of the signal, produced by wavelet transform, are used for signal structure extraction. In addition, the use of hard thresholding in the wavelet transform domain results in a separation of the nonstationary part of the input signal (heart sounds) from the stationary one (lung sounds). Thus, the location of the heart sound noise (1st and 2nd heart sound peaks) is automatically detected, without requiring any noise reference signal. Experimental results have shown that the implementation of this wavelet-based filter in lung sound analysis results in an efficient reduction of the superimposed heart sound noise, producing an almost noise-free output signal. Due to its simplicity and its fast implementation the method can easily be used in clinical medicine.

Speaker verification in noisy environments with combined spectral subtraction and missing feature theory

Abstract: In the framework of Gaussian mixture models (GMMs), we present a new approach towards robust automatic speaker verification (SV) in adverse conditions. This new and simple approach is based on the combination of speech enhancement using traditional spectral subtraction, and missing feature compensation to dynamically modify the probability computations performed in GMM recognizers. The identity of the spectral features missing due to noise masking is provided by the spectral subtraction algorithm. Previous works have demonstrated that the missing feature modeling method succeeds in speech recognition with some artificially generated interruptions, filtering and noise. We show that this method also improves noise compensation techniques used for speaker verification in more realistic conditions.

Statistical reconstruction and analysis of autoregressive signals in impulsive noise using the Gibbs sampler

Abstract: Modeling and reconstruction methods are presented for noise reduction of autocorrelated signals in non-Gaussian, impulsive noise environments. A Bayesian probabilistic framework is adopted and Markov chain Monte Carlo methods are developed for detection and correction of impulses. Individual noise sources are modeled as Gaussian with unknown scale (variance), allowing for robustness to "heavy-tailed" impulse distributions, while the underlying signal is modeled as autoregressive (AR). Results are presented for both artificial and real data from voice and music recordings, and comparisons are made with existing techniques. The new techniques are found to give improved detection and elimination of impulses in adverse noise conditions at the expense of some extra computational complexity.

Speckle noise reduction for optical coherence tomography

Abstract: Optical coherence tomography (OCT) has shown great promise for non-invasive and contact-less imaging of subsurface soft tissues. However, the problem of low image contrast caused by speckle noise has limited its applications in diagnosis. This paper present a wavelet-based method designed to improve OCT image contrast by reducing speckle noise. After transforming the image into a set of sub-images with different resolution levels in wavelet domain, we threshold high-frequency coefficients nonlinearity in horizontal, vertical, and diagonal directions. The experimental results show that wavelet processing suppresses speckle noise in OCT images of soft tissue effectively, while maintaining the sharpness of image features.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Noise reduction by paired-microphones using spectral subtraction

Abstract: This paper proposes a method of noise reduction by paired microphones as a front-end processor for speech recognition systems. This method estimates noise using a subtractive microphone array and subtracts them from the noisy speech signal using spectral subtraction (SS). Since this method can estimate noise analytically and frame by frame, it is easy to estimate noise not depending on these acoustic properties. Therefore, this method can also reduce non-stationary noise, for example sudden noise when a door has just closed, which cannot be reduced by other SS methods. The results of computer simulations and experiments in a real environment show that this method can reduce LPC log spectral envelope distortions.

An adaptive noise reduction stethoscope for auscultation in high noise environments

Abstract: Auscultation of lung sounds in patient transport vehicles such as an ambulance or aircraft is unachievable because of high ambient noise levels. Aircraft noise levels of 90–100 dB SPL are common, while lung sounds have been measured in the 22–30 dB SPL range in free space and 65–70 dB SPL within a stethoscope coupler. Also, the bandwidth of lung sounds and vehicle noise typically has significant overlap, limiting the utility of traditional band-pass filtering. In this study, a passively shielded stethoscope coupler that contains one microphone to measure the (noise-corrupted) lung sounds and another to measure the ambient noise was constructed. Lung sound measurements were made on a healthy subject in a simulated USAF C-130 aircraft environment within an acoustic chamber at noise levels ranging from 80 to 100 dB SPL. Adaptive filtering schemes using a least-mean-squares (LMS) and a normalized least-mean-squares (NLMS) approach were employed to extract the lung sounds from the noise-corrupted signal. Appro...

Low noise signal generator for use with an RFID system

Abstract: Noise reduction schemes are provided in a radio frequency identification (RFID) system for use with RFID intelligent tags. Amplitude and phase noise is minimized by starting with a low noise crystal oscillator having an output frequency which is an integer multiple n of the desired RF field frequency, and then dividing this frequency by the integer multiple n. One or more cascaded flip-flops are used for the frequency dividing. Both outputs of the final stage flip-flop are used to drive the transmitter antenna to produce a continuous wave signal.

Noise quieting with random PWM AC drives

Abstract: Acoustic noise radiated by industrial motor drives driven by PWM power electronic controllers is becoming ever more objectionable on industrial sites. The authors investigate such noise and show that the noise spectrum is closely related to the spectrum of the voltage waveform formed by the power electronics so that it may be "controlled" by controlling this voltage waveform. The paper describes a random PWM modulator and shows how it may be tailored within a prescribed band of switching frequencies to "smear" the voltage spectrum. Measured spectra and the results of listening tests are presented to show that significant perceived noise reductions are possible for relatively low switching bandwidths with but small computational overheads in the PWM generation.

A low noise, low residual offset, chopped amplifier for mixed level applications

Abstract: This paper describes the principle and the design of a CMOS low noise, low residual offset, chopped amplifier with a class AB output stage for noise and offset reduction in mixed analog digital applications. The operation is based on chopping and dynamic element matching to reduce noise and offset, without excessive increase of the charge injection residual offset. The main goal is to achieve low residual offsets by chopping at high frequencies reducing at the same time the 1/f noise of the amplifier. Measurements on a 0.8 /spl mu/m CMOS realization show reduction of 1/f noise and 18nV//spl radic/Hz residual thermal noise at low frequencies. The residual offset is lower than 100 /spl mu/V up to 8 MHz chopping frequency. Driving a 32 /spl Omega/ load the linearity is better than -80 dB and better than -88 dB for a 1 k/spl Omega/ load at 1 kHz.

Perception adaptive temporal TV-noise reduction using contour preserving prefilter techniques

Abstract: The reduction of Gaussian noise is still an important task in video systems. For this purpose a spatio-temporal noise reduction scheme for interlaced video is presented. It consists mainly of a subband based temporal recursive filter which makes use of some special properties of the human visual system. This temporal system is supported by a preceding detail preserving spatial filter with low hardware expense, which consists of an image analysing highpass filter bank and an adaptive lowpass FIR-filter for noise reduction. Both the spatial and temporal noise reduction have been evaluated with a large amount of simulations which result in a very good objective and subjective efficiency. Furthermore the chain of both temporal and spatial noise reduction may even yield results which are better than the sum of pure spatial and temporal techniques.

Noise filter for digital x-ray imaging system

Abstract: An x-ray fluorographic system produces frame images at a low dose rate for both on-line and off-line use. Background noise is filtered by first producing a mask which defines the boundaries of the structural features of interest. The mask is used to select the background pixels for filtering, while enabling the structural pixels to pass unfiltered to the display.

How to obtain high-accuracy image registration: application to movement correction of dynamic positron emission tomography data

Abstract: When registering dynamic positron emission tomography (PET) sequences, the time-dependent changes in uptake pattern prevent registration of all frames to the first frame in a straightforward manner. Instead, a sequential registration of each frame to its predecessor may be used, provided the registration algorithm is completely free of bias. It is shown that most existing algorithms introduce a bias, the size of which depends on the pixel size and the signal-to-noise ratio of the data. The bias is introduced by the pixelisation of the underlying continuous process. All existing cost-functions are more or less sensitive to noise, and the noise reduction resulting from translating one image set relative to the other means that a small movement will always be detected in the cases where no actual movement has occurred. The problem is solved by an initial resampling of the reference volume into a representation with another image and pixel size. If the new representation is sensibly chosen it means that all possible transforms applied to the other image volume will yield approximately the same noise reduction, thereby removing the source of the bias. The described effect is demonstrated on phantom data, and its impact is shown on human data.

A New Rational Approach to Jet Noise Reduction

Abstract: This paper offers a new rational approach to jet noise suppression methodology. The tools required to implement such an approach are discussed. These involve the use of global velocimetry to measure those Lighthill turbulent stress tensor terms thought most important to noise generation. The framework of the dynamic systems model as it applies to the development of a noise suppression model is discussed, as well as the latest results on the development of an actuator for control input. The dynamic systems model offers a unique opportunity to study the influence of a concept noise reduction scheme on noise reduction through appropriate algorithms that relate turbulent jet processes to noise.

Active acoustic noise reduction system

Abstract: An active acoustic noise reduction system which comprises a single input transducer and an output actuator that are physically located next to each other in the same location. In one embodiment, the input transducer and the output actuator are a hybrid represented by a single element. The active noise reduction system is located as close as possible to the noise source and functions to generate an antinoise cancellation sound wave with minimum delay and opposite phase with respect to the noise source. The noise reduction system also comprises a non linearity correction circuit, a delayed cancellation circuit and variable gain amplifier. The system provides user control of the quiet zones generated by the system by varying the gain of the variable gain amplifier. The system provides a user with the ability In one embodiment, an echo canceler is utilized to remove echoes fed back from the output actuator. In another embodiment, an input decoder is used instead of an echo canceler to remove feedback picked up from the output actuator.

Review of feedback and feedforward noise reduction techniques

Abstract: Noise reduction techniques based on both feedback and feedforward topologies have been employed over the last few decades to improve phase and amplitude noise of devices and oscillators. Various techniques, both historical and state-of-the-art, are compared in terms of noise performance, circuit complexity and applicability. A comprehensive reference list is included.

AEM noise reduction with remote referencing

Abstract: A number of sources contribute to noise in airborne electromagnetic (AEM) systems. The main source of noise at low frequencies (below about 1 kHz) is motion of the bird receiver coils in the earth's magnetic field. Generally, the main noise remaining after reduction of motion noise is caused by sferics spikes produced by lightning activity. Other external sources that produce noise in AEM systems include power lines and VLF transmitters. The characteristics of sferics noise recorded with a ground-based system with two receiver stations studied at a number of localities throughout Australia showed that a high degree of spatial correlation exists between the three vector components of the noise and also between noise measured simultaneously at two stations with a separation at least as large as 50 km. Sferics in the high-frequency range (~2 to 100 kHz) were found to correlate with data recorded at a remote station. Using simple subtraction of noise time series measured at the remote station from the corresponding local time series, a noise reduction factor of about 4 was obtained. Other strategies for noise reduction include prediction filtering using either local or remote referencing. By reducing noise in AEM data, target detection depth can be increased and stacking time can be decreased, improving spatial resolution. These two strategies have important implications for AEM surveys, since stacking time is always limited because of the continual travel of the receiver along a flight line. Noise produced by other external sources, in particular, noise produced by VLF transmitters and 50 Hz powerline noise can also be reduced through referencing. The continual monitoring of noise with remote referencing permits changes in amplitude or frequency of noise from these sources to be accommodated in the noise reduction process.

Noise reduction of page-oriented data storage by inverse filtering during recording

Abstract: Two novel techniques for eliminating deterministic noise from a page-oriented memory are presented. The first technique equalizes the output response of ON pixels by adjustment of the exposure of each pixel during the recording of each data page. A test image transmitted through the system measures the spatial nonuniformities, and the appropriate inverse filter is imposed upon the data page and recorded in the storage material. On readout, the output signal values are then spatially uniform, perturbed only by random noise sources. Experimental results of using this predistortion technique in a pixel-matched holographic storage system are shown. Under conditions of high volumetric density, raw bit-error-rate (BER) improvements of 6–8??orders of magnitude are obtained (from 10-4 to <10-10). The second technique uses a phase shift during holographic storage to subtract from bright OFF pixels. Under conditions of low spatial light modulator contrast, BER improvements of 6??orders of magnitude (from 10-2 to 10-8) are demonstrated.