An Image Reconstruction Method Based on Total Variation and Wavelet Tight Frame for Limited-Angle CT

Limited-angle computed tomography (CT) reconstruction problem is an ill-posed inverse problem. Currently, regularized CT reconstructions are usually considered by incorporating the total variation (TV) norm of an image into data fidelity term. However, the reconstructed images may be degraded using the TV-based minimization method with limited-angle artifacts. In recent years, the theory of wavelet tight frame has been well developed and has some advantages in preserving the sharp features as well as smoothness. To further improve the quality of reconstructed images, we propose an image reconstruction method incorporating TV with wavelet tight frame for limited-angle CT problem, which objective function includes ℓ
₁
and ℓ
₀
regularization terms and solved by a TV-based simultaneous algebraic reconstruction technique and an alternating direction method of multipliers. Compared with some TV-based reconstruction methods, the experimental results show that our method can further improve the quality of reconstructed images and suppress the limited-angle artifacts as well as preserve the low-contrast objects.