This paper proposes an algorithm to reconstruct a High Resolution (HR) image from a set of blurred, warped, undersampled, and noisy measured images. The proposed algorithm uses the affine block-based algorithm in the maximum likelihood (ML) estimator. It is tested using synthetic images, where the reconstructed image can be compared with its original. A number of experiments were performed with