Image deconvolution with total variation bounds

Total variation has been used exclusively as an objective in the formulation of image deconvolution problems. In this paper, we propose an alternative framework in which total variation is used as a constraint. In contrast with the standard approach, this framework requires an a priori bound on the total variation of the original image, while no a priori information on the noise is necessary. Furthermore, it places no limitation on the incorporation of additional constraints in the recovery process and can be solved efficiently via powerful block-iterative methods.