Application of Alternate Iterative Algorithm to Image Restoration

For overcoming the disadvantage of total variation for regularization, which easily produces stair effect, an improved weight energy functional regularization model and alternate algorithm is proposed. Because of non-smooth property of total variation semi-norm regularization model, it is impossible to solve primal model directly. For solving the problem, taking advantage of Fenchel transform, the primal model is converted into dual model, resorting to variable splitting technology, the alternating iterative algorithm is deduced. Moreover, the step length updating principle of primal-dual variable is given. Finally, using Camera image blurred by Gaussian noise, Telescope image blurred by system and Poisson noise for image restoration, simulations show the proposed can achieve smaller relative error, deviation error, higher peak of signal-to-noise ratio, and better visual effect.