Sparse image representation for jet neutron and gamma tomography

Highlights: •A new tomographic method for the reconstruction of the 2-D neutron and gamma emissivity on JET. •The method is based on the sparse representation of the reconstructed image in an over-complete dictionary. •Several techniques, based on a priori information are used to regularize this highly limited data set tomographic problem. •The proposed method provides good reconstructions in terms of shapes and resolution. -- Abstract: The JET gamma/neutron profile monitor plasma coverage of the emissive region enables tomographic reconstruction. However, due to the availability of only two projection angles and to the coarse sampling, tomography is a highly limited data set problem. A new reconstruction method, based on the sparse representation of the reconstructed image in an over-complete dictionary, has been developed and applied to JET neutron/gamma tomography. The method has been tested on JET experimental data and significant results are presented. The proposed method provides good reconstructions in terms of shapes and resolution