Adaptive Reconstruction of Discrete-Valued Objects from few Projections

Recently, we proposed an algorithm for binary tomography based on DC ( difference of convex functions ) programming [13,15]. In this paper, we extend the binary reconstruction problem to multi-valued objects. We describe how such objects can be reconstructed just by combining binary decisions. The proposed algorithm remains practicable for multi-valued reconstructions, and even with a large number of discrete values. Furthermore, we show how approximately known absorption levels can be adaptively estimated within the reconstruction process.