  Dual spectral computed tomography (DSCT) can achieve energy- and
material-selective images, and has a superior distinguishability of some
materials than conventional single spectral computed tomography (SSCT).
However, the decomposition process is illposed, which is sensitive with noise,
thus the quality of decomposed images are usually degraded, especially the
signal-to-noise ratio (SNR) is much lower than single spectra based directly
reconstructions. In this work, we first establish a local linear relationship
between dual spectra based decomposed results and single spectra based directly
reconstructed images. Then, based on this constraint, we propose an
optimization model for DSCT and develop a guided image filtering based
iterative solution method. Both simulated and real experiments are provided to
validate the effectiveness of the proposed approach.
