It has been lately shown that noise tracking and speech denoising can be improved by a postprocessor established on a maximum a-posteriori based (MAP-B) noise power spectral density (PSD) estimation algorithm. In the current contribution we investigate the MAP-B estimator by carrying out a quality analysis comprising the following three steps. First, we analyse the estimator with respect to unb...

Monitoring ocean acoustic noise has been the subject of considerable recent study, motivated by the desire to assess the impact of anthropogenic noise on marine life. A combination of measuring ocean sound using an acoustic sensor network and modelling sources of sound and sound propagation has been proposed as an approach to estimating the acoustic noise map within a region of interest. Howeve...

We study destriping as a map-making method for temperature-and-polarization data for cosmic microwave background observations. We present a particular implementation of destriping and study the residual error in output maps, using simulated data corresponding to the 70 GHz channel of the Planck satellite, but assuming idealized detector and beam properties. The relevant residual map is the diff...

A problem of image denoising, when images are corrupted by a non-stationary noise, is considered in this paper. Since, practice, no priori information on noise available, statistics should be pre-estimated prior to denoising. In paper, deep convolutional neural network (CNN) based method for estimation map local, patch-wise, standard deviations (so-called <italic xmlns:mml="http://www.w3.org/19...

In order to understand the capabilities and limitations of quantum computers, it is necessary develop methods that efficiently characterize benchmark error channels present on these devices. this paper, we a method faithfully reconstructs marginal (local) approximation effective noise (MATEN) channel, acts as single layer at end circuit. We first introduce dual map framework allows us analytica...

In this paper, we present a Stationary Wavelet Transform (SWT) based method for the purpose of despeckling the Synthetic Aperture radar (SAR) images by applying a maximum a posteriori probability (MAP) condition to estimate the noise free wavelet coefficients. A MAP Estimator is designed for this purpose which uses Rayleigh distribution for modeling the speckle noise and Laplacian distribution ...