In this paper we consider the problem of parametric estimation of a linear model corrupted by measurement error. In order to take into account the biasing effects caused by the presence of an external source of error, we propose an adjustmeni to the least square estimator. The statistical properties of the adjusted estimator are then experimentally verified with respect to two models characterising the literature of images analysis.
Adjusted Least Square estimation for Noisy Images
ROMAGNOLI, Luca
2004-01-01
Abstract
In this paper we consider the problem of parametric estimation of a linear model corrupted by measurement error. In order to take into account the biasing effects caused by the presence of an external source of error, we propose an adjustmeni to the least square estimator. The statistical properties of the adjusted estimator are then experimentally verified with respect to two models characterising the literature of images analysis.File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
