Noise reduction

About: Noise reduction is a research topic. Over the lifetime, 25121 publications have been published within this topic receiving 300815 citations. The topic is also known as: denoising & noise removal.

Speckle-constrained filtering of ultrasound images

Abstract: Ultrasound images provide the clinician with non-invasive, low cost, and real-time images that can help them in diagnosis, planning and therapy. However, although the human eye is able to derive the meaningful information from these images, automatic processing is very difficult because of the noise and artefacts present in the image. In this work, we propose to extend the current anisotropic diffusion technique to deal with the speckle noise present in the Ultrasound images. To this end, we use a previously derived model of the noise, and we write the restoration scheme as a energy minimization constrained by the noise model and parameters. This approach leads to a new data attachment term whose optimal weight can be automatically estimated.

Biased motion-adaptive temporal filtering for speckle reduction in echocardiography

Abstract: Describes a new fully motion-adaptive spatio-temporal filtering technique to reduce the speckle in ultrasound images. The advantages of this approach are demonstrated in echocardiographic boundary detection and in comparison with other techniques. The first stage of many automated echocardiographic image interpretation schemes is filtering to reduce the amount of speckle noise. The authors show how the two-dimensional least mean squares (TDLMS) filter can be configured as a motion-compensated filter for a time sequence of ultrasound images that eliminates the blurring associated with direct averaging. For an image corrupted by multiplicative speckle noise, the mode of the intensity distribution approximates the maximum likelihood estimator. In consequence, the temporal filter's output is biased towards the mode from the mean, using information contained within the speckle itself. A new adaptive algorithm for controlling the filter's convergence is also included. To evaluate performance, application to simulated, phantom, and an in vivo test sequence of the carotid artery are considered in comparison with other techniques. The effect of filtering on edges is of great importance, as these are used by subsequent image interpretation schemes. Quantitative measurements demonstrate the effectiveness of the Biased TDLMS filter, for both noise reduction and edge preservation. Echocardiographic images have a high noise content and suffer from poor contrast. Despite this challenging environment, the Biased TDLMS filter is shown to produce images that are better inputs for subsequent feature extraction. The benefits for echocardiographic images are highlighted by considering the problems of mitral valve analysis and extraction of the left atrium boundary.

Multi-microphone speech dereverberation and noise reduction using relative early transfer functions

Abstract: In speech communication systems, the microphone signals are degraded by reverberation and ambient noise. The reverberant speech can be separated into two components, namely, an early speech component that includes the direct path and some early reflections, and a late reverberant component that includes all the late reflections. In this paper, a novel algorithm to simultaneously suppress early reflections, late reverberation and ambient noise is presented. A multi-microphone minimum mean square error estimator is used to obtain a spatially filtered vaersion of the early speech component. The estimator constructed as a minimum variance distortionless response (MVDR) beam-former (BF) followed by a postfilter (PF). Three unique design features characterize the proposed method. First, the MVDR BF is implemented in a special structure, named the nonorthogonal generalized sidelobe canceller (NO-GSC). Compared with the more conventional orthogonal GSC structure, the new structure allows for a simpler implementation of the GSC blocks for various MVDR constraints. Second, In contrast to earlier works, RETFs are used in the MVDR criterion rather than either the entire RTFs or only the direct-path of the desired speech signal. An estimator of the RETFs is proposed as well. Third, the late reverberation and noise are processed by both the beamforming stage and the PF stage. Since the relative power of the noise and the late reverberation varies with the frame index, a computationally efficient method for the required matrix inversion is proposed to circumvent the cumbersome mathematical operation. The algorithm was evaluated and compared with two alternative multichannel algorithms and one single-channel algorithm using simulated data and data recorded in a room with a reverberation time of 0.5 s for various source-microphone array distances (1-4 m) and several signal-to-noise levels. The processed signals were tested using two commonly used objective measures, namely perceptual evaluation of speech quality and log-spectral distance. As an additional objective measure, the improvement in word accuracy percentage of an acoustic speech recognition system is also demonstrated.

Using the coherence function for noise reduction

Abstract: With the development of hands-free radio communications there is great interest in noise cancelling or speech enhancement in a car. The authors assume that M observations are available; each one is composed of signal and noise (s/sub i/+b/sub i/), and s/sub 1/ is the signal to be estimated. Whatever the distance between microphones is, the signals are strongly correlated, while the correlation between noises becomes rather weak for a sufficiently great distance. The coherence function is then a pertinent criterion to know whether a speech signal exists or not. The three methods presented use the coherence function to filter the observations so giving an estimate of the signal s/sub 1/. The procedures presented are first shown for M=2. Then, a generalisation of these procedures is offered. The performances of the three methods have been evaluated on real noisy speech signals by objective tests (gain on the signal-to-noise ratio, distance measures) and informal listening tests.< >

Combined homomorphic and local-statistics processing for restoration of images degraded by signal-dependent noise.

Abstract: The generalized homomorphic transformation to make signal-dependent noise independent of the signal is combined with a local-statistics image restoration technique to process images degraded by signal-dependent noise. Experimental results are given for images degraded by film-grain noise and by multiplicative noise.