Recursive enhancement of noncausal images

A recursive procedure is implemented for the enhancement of noncausal Gauss Markov random fields. Experimental results for the enhancement of synthetic as well as real images corrupted by additive white Gaussian noise are provided. These are contrasted with equivalent results obtained by processing the images with recursive filters derived by imposing a causality constraint upon the fields. The results show that the noncausal recursors provide considerable reduction in the mean square error (MSE) of the noisy images without the introduction of undesirable visual effects, such as streaking, that are produced when causality constraints are imposed.<<ETX>>