Regularized image up-sampling using a new observation model and the level set method

This paper presents a new formulation of the regularized image up-sampling problem that incorporates models of the image acquisition and display processes. This approach leads to a new data fidelity term that has been coupled with a bounded-total-variation regularizer to yield our objective function. This objective function is minimized using the level-set method with two types of motion that interact simultaneously. The method was implemented and has been verified to provide good results, yielding crisp edges without introducing ringing or other artifacts.