Generation of “Similar” Images from a Given Discrete Image
Boris Kozintsev, Benjamin Kedem · Journal of Computational and Graphical Statistics · 2000
A discrete image of several colors is viewed as a discrete random field obtained by clipping or quantizing a Gaussian random field at several levels. Given a discrete image, parameters of the unobserved original Gaussian random field are estimated. Discrete images, statistically similar to the original image, are then obtained by generating different realizations of the Gaussian field and clipping them. To overcome the computational difficulties, the block Toeplitz covariance matrix of the Gaussian field is embedded into a block circulant matrix which is diagonalized by the fast Fourier transform. The Gibbs sampler is used to apply the stochastic EM algorithm for the estimation of the field's parameters.