SVD pseudoinversion image reconstruction

The singular value decomposition (SVD) pseudoinversion method has been applied to image reconstruction from projections. In this paper, two SVD pseudoinversion methods are discussed in the search for optimum restoration; one uses Wiener filtering and the other uses truncated inverse filtering. These methods partly overcome the ill-conditioned nature of reconstruction problems by trading off between noise and signal quality. Using computer simulation, the present SVD method was compared with the conventional Fourier convolution method. Results are presented together with some limitations peculiar to the application of this method for image reconstruction and restoration.