Preconditioned Conjugate Gradient Method for Boundary Artifact-Free Image Deblurring
نویسندگان
چکیده
Several methods have been proposed to reduce boundary artifacts in image deblurring. Some of those methods impose certain assumptions on image pixels outside the field-of-view; the most important of these assume reflective or anti-reflective boundary conditions. Boundary condition methods, including reflective and anti-reflective ones, however, often fail to reduce boundary artifacts, and, in some cases, generate their own artifacts, especially when the image to be deblurred does not accurately satisfy the imposed condition. To overcome these difficulties, we suggest using free boundary conditions, which do not impose any restrictions on image pixels outside the field-of-view, and preconditioned conjugate gradient methods, where preconditioners are designed to compensate for the non-uniformity in contributions from image pixels to the observation. Our simulation studies show that the proposed method outperforms reflective and anti-reflective boundary condition methods in removing boundary artifacts. The simulation studies also show that the proposed method can be applicable to arbitrarily shaped images and has the benefit of recovering damaged parts in blurred images.
منابع مشابه
Superoptimal Preconditioned Conjugate Gradient Iteration for Image Deblurring
We study the superoptimal Frobenius operators in the two-level circulant algebra. We consider two specific viewpoints: (1) the regularizing properties in imaging and (2) the computational effort in connection with the preconditioned conjugate gradient method. Some numerical experiments illustrating the effectiveness of the proposed technique are given and discussed.
متن کاملPreconditioners for Linear Systems Arising in Image Reconstruction
For the numerical solution of large linear systems, the preconditioned conjugate gradient algorithm can be very eeective if one has a good preconditioner. Two distinctly diierent approaches to preconditioning are discussed for solving systems derived from continuous linear operators of the form ~ K + L, where ~ K is a convolution operator, L is a regularization operator, and is a small positive...
متن کاملFast Preconditioners for Total Variation Deblurring with Antireflective Boundary Conditions
In recent works several authors have proposed the use of precise boundary conditions (BCs) for blurring models and they proved that the resulting choice (Neumann or reflective, antireflective) leads to fast algorithms both for deblurring and for detecting the regularization parameters in presence of noise. When considering a symmetric point spread function, the crucial fact is that such BCs are...
متن کاملFast Motion Deblurring Using Conjugate Gradient Based Minimization Approach
2 [email protected] ________________________________________________________________________________ ABSTRACT We propose a new algorithm for removing a fast motion blur from an image. The term "iterative met hod" refers to a wide range of techniques which use successive approximations to obtain more accurate solutions .In this paper an attempt to solve systems of linear equations of the form ...
متن کاملArnoldi methods for image deblurring with anti-reflective boundary conditions
Image deblurring with anti-reflective boundary conditions and a non-symmetric point spread function is considered. Several iterative methods based on Krylov subspace projections, as well as Arnoldi-Tikhonov regularization methods, with reblurring right or left preconditioners are compared. The aim of the preconditioner is not to accelerate the convergence, but to improve the quality of the comp...
متن کامل