On the concept of a local greyvalue distribution and the adaptive estimation of a structure tensor

Abstract

As a step towards a local analysis of local image features, the position, peak value, and covariance matrix of an isolated, noise-free multivariate Gaussian are determined in closed form from four ‘observables’, computed by gaussian-weighted averaging first and second powers of (up to second order) partial derivatives of a digitized greyvalue distribution.