Reconstructing Some hv-Convex Binary Images from Three or Four Projections

Abstract

The reconstruction of binary images from their projections is an important problem in discrete tomography. The main challenge in this task is that in certain cases the projections do not uniquely determine the binary image. This can yield an extremely large number of (sometimes very different) solutions. Moreover, under certain circumstances the reconstruction becomes NP-hard. A commonly used technique to reduce ambiguity and to avoid intractability is to suppose that the image to be reconstructed arises from a certain class of images having some geometrical properties. This paper studies the reconstruction problem in the class of hv-convex images having their components in so-called decomposable configurations. First, we give a negative result showing that there can be exponentially many images of the above class having the same three projections. Then, we present a heuristic that uses four projections to reconstruct an hv-convex image with decomposable configuration. We also analyze the performance of our heuristic from the viewpoints of accuracy and running time.