Adaptive Box-Constrained Total Variation Image Restoration Using Iterative Regularization Parameter Adjustment Method

Abstract

In this paper, we consider the problem of image restoration with box-constraints. Image restoration problem is ill-conditioned and the regularization approach has widely been used to stabilize the solution. The restored image highly depends on the choice of the regularization parameter. The regularization parameter is generally determined by trial-and-error method when no true original image is available. Obviously, it is time consuming. The main aim in this paper is to develop an algorithm to choose the regularization parameter automatically when the box-constraints are imposed. In the proposed algorithm, the regularization parameter is adaptively determined by the previous iterative solution. Numerical simulations are used to demonstrate the performance of the proposed method.

Variable Splitting Based Method for Image Restoration with Impulse Plus Gaussian Noise

“…Hence, the recursions for -, -, and -related subproblems can be regained accordingly. Generally, those skills on penalties can numerically render impressive performance (see, e.g., [7,31,32] and references therein).…”