Abstract: Super-resolution reconstruction has been a very hot research topic currently. In this paper, we study a fast decoupling algorithm for TV-based (Total variation) image super-resolution reconstruction. A new TV-based decoupling model is proposed by utilizing the half-quadratic regularization approach. The treatment is separated into measurements fusion, deblurring and denoising by exploiting the alternating minimization algorithm and the property of the space-invariance blur. The fusion part is shown to be a very simple non-iterative algorithm. The deblurring part can be solved by transform-based preconditioning conjugate gradient method for improved convergence. The subspace projection method is employed to solve the denoising problem. The proposed algorithm reduces the computational complexity. Super-resolution experiment results demonstrate that the proposed algorithm is not only able to restrain the noise and preserve the important geometric structures in the image such as edges, but also able to maintain the fidelity of flat regions without producing the staircase effect.