In Micro-CT systems

further improvement of the spatial resolution of the reconstructed images is limited by the X-ray dose level

the pixel pitch

and the aperture of the detector element.In this paper

we study a total variation (TV) based optimization model for Micro-CT reconstruction based on an up-sampling of the reconstruction grid with original detector and X-ray dose.Using an extension of the gradient projection method

an alternating minimization algorithm is employed to solve the corresponding energy function.In the process of the minimization

the treatment is separated into the gradient step of the fit-to-data term

the total variation (TV) denoising

and the specific linear combination of the previous two points.Experiments on simulated data as well as real Micro-CT data are performed.Our results show that the proposed approach can dramatically improve the spatial resolution of the reconstructed images compared to the conventional Filter Back-Projection algorithm.