Angular upsampling of projection measurements in 3D computed tomography using a sparsity prior

We propose an algorithm for angular upsampling of the projections in 3D computed tomography (CT). The central assumption of the proposed method is that small blocks extracted from stacked projections have a sparse representation in an overcomplete dictionary. We present methods for fast solution of the optimization problems involved and apply the proposed algorithm on simulated and real projections. Our results show that upsampling of the projections with the proposed method can lead to a significant improvement in the quality of the reconstructed image.