It is well known that linear predictive coding (LPC) is sensitive to additive noise and that the corresponding noise compensation method suffers from poor accuracy of noise power estimation. In this paper, a novel noise compensation LPC method based on pitch synchronous analysis is presented. Using the proposed method, a more accurate estimation of noise power is calculated on each current fram...

We put forth in this paper a geometrically motivated 3-D motion error analysis which is capable of supporting investigation of global effect such as inherent ambiguities. The error expression that we derive allows us to predict the exact conditions likely to cause ambiguities and how these ambiguities vary with motion types such as lateral or forward motion. Our formulation, though geometricall...

In this paper, we address the problem of the restoration of images which have been affected by impulse noise or by a mixture of Gaussian and impulse noise. We rely on a patch-based approach, which requires careful choices for both the distance between patches and for the statistical estimator of the original patch. Experiments are led in the case of pure impulse noise and in the case of a mixtu...

In this paper, we describe a new and computationally efficient adaptive system for the enhancement of autoregressive (AR) signals which are disturbed by additive white or colored noise and impulsive noise. The system is comprised of an adaptive Kalman filter operating as a fixed lag smoother and a subsystem for AR parameter estimation. A superior performance is achieved by implementing a feedba...

Performances of speech enhancement algorithms depend greatly on the accuracy of the estimated noise. In this paper, we explain in details the relationship between noise estimation and denoised speech quality. Firstly, the effect of silence length on noise estimation is analyzed. We particularly show the importance of noise smoothing over frames on denoising quality. This study leads to the deve...

Estimation on a noisy signal observed by a nonlinear sensor taking the form of a threshold quantizer is considered. The optimal Bayesian estimator with minimal error is derived in this nonlinear setting. The existence of conditions where the performance of this estimator can be improved by raising the level of noise is established, both theoretically and numerically. These results constitute a ...

Of the many measures that characterize the performance of a communication receiver, signal-to-noise ratio (SNR) is perhaps the most fundamental in that many of the other measures directly depend on its knowledge for their evaluation. In the design of receivers for autonomous operation, it is desirable that the estimation of SNR take place with as little known information as possible regarding o...

Figure 3: The distribution of the estimated noise in an image (Lenna) to which noise with a uniform shaped distribution is added. Also shown are the true noise distribution and the theoretically estimated distribution. The latter is obtained by convolving the (truncated) uniform function with a normal function.

Almost estimators are designed for the white observation noise. In the estimation problems, rather than the white observation noise, there might be actual cases where the observation noise is modeled by the colored noise process. This paper examines to design a new estimation technique of recursive least-squares (RLS) Wiener fixed-point smoother and filter for colored observation noise in linea...

The determination of Cramer-Rao lower bound (CRLB) as an optimality criterion for the problem of channel estimation in wireless communication is a very important issue. Several CRLBs on channel estimation have been derived for Gaussian noise. However, a practical channel is affected by not only Gaussian background noise but also non-Gaussian noise such as impulsive interference. This paper deri...