1. A method for modeling an image comprising the steps of: tiling an image at a predetermined scale to form small tile segments of the image; combining the small segments of the image into a data matrix extracting principal components of the data matrix in terms of principal component feature tiles; generating a set of coefficient weights corresponding to the principal component tiles; scaling the principal component tiles to reduce the data therewith; transmitting from a transmitting side the scaled principal component tiles and the weights associated with each image segment to a remote location; interpolating the principal component tiles at the remote location to obtain full-scale principal component tiles; computing a weighted sum of full-scale principal component tiles for each segment to obtain a coarse image at full scale; constructing a coarse image at the transmitting side; obtaining the difference between the original image and the coarse image at the transmitting side to obtain a residual image; selecting a finer scale for the residual image; producing finer scale residual image tiles from the finer scale residual image; obtaining from the finer scale residual image tiles a finer set of principal component tiles; forming a weighted sum of the finer-scaled principal component tiles to represent each residual image segment; transmitting to the remote location the newly-obtained finer principal component tiles and the new weights associated with each residual image segment; reconstructing the residual image at the remote location from the transmitted new, finer principal component tiles and the new weights associated therewith; and, at the remote location summing the coarse and residual images to obtain an improved image representation.