  The localized radial symmetric function, or blob, is an ideal alternative to
the pixel basis for X-ray computed tomography (CT) image reconstruction. In
this paper we develop image representation models using blob, and propose
reconstruction methods for few projections data. The image is represented in a
shift invariant space generated by a Gaussian blob or a multiscale blob system
of different frequency selectivity, and the reconstruction is done through
minimizing the Total Variation or the 1 norm of blob coefficients. Some 2D
numerical results are presented, where we use GPU platform for accelerating the
X-ray projection and back-projection, the interpolation and the gradient
computations.
