Convex projections algorithm for restoration of limited-angle chromotomographic images

We present a new algorithm for image restoration in limited-angle chromotom ography. The algorithm is a generalization of the technique considered prev iously by the authors, based on a hybrid of a direct method of inversion an d the iterative method of projections onto convex sets. The generalization is achieved by introducing a new object domain constraint. This constraint takes advantage of hyperspectral data redundancy and is realized by truncat ing the singular-value decomposition of the spatial-chromatic image matrix. As previously, the transform domain constraint is defined in terms of nonz ero singular values of the system transfer function matrix. The new algorit hm delivers high image fidelity, converges rapidly, and is easy to implemen t. Results of experiments on real data are included. (C) 1999 Optical Socie ty of America [S0740-3232(99)00802-9].