1 research outputs found
Image Restoration by Iterative Denoising and Backward Projections
Inverse problems appear in many applications, such as image deblurring and
inpainting. The common approach to address them is to design a specific
algorithm for each problem. The Plug-and-Play (P&P) framework, which has been
recently introduced, allows solving general inverse problems by leveraging the
impressive capabilities of existing denoising algorithms. While this fresh
strategy has found many applications, a burdensome parameter tuning is often
required in order to obtain high-quality results. In this work, we propose an
alternative method for solving inverse problems using off-the-shelf denoisers,
which requires less parameter tuning. First, we transform a typical cost
function, composed of fidelity and prior terms, into a closely related, novel
optimization problem. Then, we propose an efficient minimization scheme with a
plug-and-play property, i.e., the prior term is handled solely by a denoising
operation. Finally, we present an automatic tuning mechanism to set the
method's parameters. We provide a theoretical analysis of the method, and
empirically demonstrate its competitiveness with task-specific techniques and
the P&P approach for image inpainting and deblurring.Comment: To appear in IEEE Transactions on Image Processin