Enhancement of Noisy Images Using an Interpolative Model in Two Dimensions

The use of two-dimensional interpolative models for recursive enhancement of noisy images is considered. The two-dimensional data is decorrelated either row-wise or column-wise to obtain an equivalent one-dimensional interpolative model. An adaptive identification scheme to identify the parameters of the model is presented which are then used in a simple estimation scheme for recovering the image data. A modification of the FFT algorithm as well as the DCT algorithm are used in decorrelating the data. The performance of these transforms for the present application is compared in terms of the number of computations required and the mean-square error between the enhanced image and the original noise-free image. Several examples are presented to illustrate the applicability of the algorithm.