Area Estimation of Stochastic Objects from an Image Containing a Background
A. P. Trifonov, Y. N. Pribytkov
Keywords: Gaussian image, background, spatial noise, unknown area, applicative model, efficiency of area estimator
Pages: 49-57
Abstract
Maximum likelihood algorithms for estimating the area of stochastic images against a stochastic background in the presence of spatial noise are synthesized. A comparison is made of area estimation algorithms based on the additive and applicative models of interaction between the image and background. Asymptotic expressions for the characteristics of the area estimators are obtained. The effect of the difference between the statistical characteristics of the background and image on the accuracy of image area estimation is studied
|
