1. A method of enhancing contours in a noisy image, said method comprising the steps of: a) capturing said noisy image as a first distribution m of spatially distributed intensity values b) transforming said intensity values of said first distribution m into a second distribution U of spatially distributed intensity values representing an enhanced image having enhanced contours therein, by using a transformation model, which defines a cubic filter, as follows: U&equals;a 0 &plus;a 3 &lsqb;Gm&plus;G*m&rsqb;&plus;a 2 &lsqb;G (diag m ) Gm&plus;Gm·G*m&plus;G* (diag m ) G*m&rsqb; &plus;a 1 &lsqb;G (diag m ) G (diag m ) Gm&plus;G (diag m ) Gm·G*m&plus;Gm·G* (diag m ) G*m &plus;G* (diag m ) G* (diag m ) G*m&rsqb;, where: diag m is a diagonal operator comprising a matrix with said first distribution m along the diagonal of said matrix and zeroes elsewhere; the operation “·” indicates the taking of a componentwise product of two vectors, wherein in s·v evaluated at location r is the product of the two numbers s(r) and v(r), where s and v are each functions of r, a 0, a 1, a 2, and a 3 are real-valued parameters controlling the relative importance of constant, linear, quadratic, and cubic terms, respectively, in said transformation model; G&equals;G(r 1, r 2 ) comprises a matrix of probabilities, each entry of which represents the probability that a contour passing through location r 1 passes through location r 2 in a forward direction along said contour; and G*&equals;G*(r 1, r 2 ) comprises a matrix of probabilities, each entry of which represents the probability that a contour passing through location r 1 passes through location r 2 in a backward direction along said contour.