This project revisits the image restoration issue. The idea is that minimizing the l1 norm of the discrete gradient of a damaged image yields an output that is barely noticeable from the original non-degraded form. The inpainting problem was formulated to limit the high fidelity of known observations and minimize the overall norm of variability.
