A comparative study to select an image deconvolution method

Image deconvolution is an important subject in image processing. It is an ill-posed inverse problem, so regularization techniques are used to solve this problem by adding constraints to the objective function. Various popular algorithms have been developed to solve such problem. This paper studies various approaches to the nonlinear degraded images restoration problem which are useful in many images enhancement applications. Swarm intelligence is applied for total variation (TV) minimization, instead of the standard Tikhonov regularization method which is often used. In this work, we attempt to reconstruct or recover corrupted images that have been degraded during acquisition; using some a priori knowledge of the degradation phenomenon. The truncated singular value decomposition (TSVD) method is also considered for image deconvolution in this paper. A comparison between these methods made on examples is included.