This paper deals with arrival time estimation of a narrow-band signal disturbed by white gaussian noise. In order to estimate the distance between a transmitting source and a reflecting target an estimator, based on the criterion of minimum mean square error (MMSE), is investigated. The MMSE-estimator is implemented in an experimental ultrasound pulse-echo system, and results of comparative sim...

Removing noise from images is a challenging problem in digital image processing. This paper presents an image denoising method based on a maximum a posteriori (MAP) density function estimator, which is implemented in the wavelet domain because of its energy compaction property. The performance of the MAP estimator depends on the proposed model for noise-free wavelet coefficients. Thus in the wa...

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. The solution of the MAP estimator is based on the assumption that the wavelet coefficients have a known distribution. Rayleigh distribut...

We present the first detailed case study using quadratic estimators (QE) to diagnose and remove systematics in observed Cosmic Microwave Background (CMB) maps. In this work we focus on temperature polarization leakage. use an iterative QE analysis systematics, analogy de-lensing, recovering primordial B-mode signal systematic introduce a new Gaussian filtering scheme crucial stable convergence ...

Estimation of a covariance matrix or its inverse plays a central role in many statistical methods. For these methods to work reliably, estimated matrices must not only be invertible but also well-conditioned. The current paper introduces a novel prior to ensure a well-conditioned maximum a posteriori (MAP) covariance estimate. The prior shrinks the sample covariance estimator towards a stable t...

The paper is focused on Digital Elevation Model (DEM) reconstruction from differential interferometry synthetic aperture radar (DInSAR). In doing so, conventional DInSAR procedures are implemented to three repeat passes of RADARSAT-1 SAR fine mode data (F1). Further, the multichannel MAP height estimator is implemented with phase unwrapping technique. Consequently, the multichannel MAP height e...

Markov or a maximum entropy random field model for a prior distribution may be viewed as a minimizer of a variational problem. Using notions from robust statistics, a variational filter referred to as a Huber gradient descent flow is proposed. It is a result of optimizing a Huber functional subject to some noise constraints and takes a hybrid form of a total variation diffusion for large gradie...

We consider the Bayesian inference of a random Gaussian vector in a linear model with a Gaussian model matrix. We derive the maximum a-posteriori (MAP) estimator for this model and show that it can be found using a simple line search over a unimodal function that can be efficiently evaluated. Next, we discuss the application of this estimator in the context of nearoptimal detection of near-Gaus...

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 ...

An aggregation rule maps each profile of individual strict preference orderings over a set of alternatives into a social ordering over that set. We call such a rule strategyproof if misreporting one’s preference never produces a different social ordering that is between the original ordering and one’s own preference. After describing two examples of manipulable rules, we study in some detail th...