Abstract—In this article, two closed and convex sets for blind deconvolution problem are proposed. Most blurring functions in microscopy are symmetric with respect to the origin. Therefore, they do not modify the phase of the Fourier transform (FT) of the original image. As a result blurred image and the original image have the same FT phase. Therefore, the set of images with a prescribed FT phase can be used as a constraint set in blind deconvolution problems. Another convex set that can be used during the image reconstruction process is the Epigraph Set of Total Variation (ESTV) function. This set does not need a prescribed upper bound on the total variation of the image. The upper bound is automatically adjusted according to the current ...
International audienceBlind image deconvolution recovers a deblurred image and the blur kernel from ...
Blurred image restoration poses a great challenge under the non-Gaussian noise environments in vario...
Image deblurring has long been modeled as a deconvolution problem. In the literature, the point-spre...
Abstract—In this article, two closed and convex sets for blind deconvolution problem are proposed. M...
The need for image restoration arises in many applications of various scientific disciplines, such a...
AbstractThe need for image restoration arises in many applications of various scientific disciplines...
In this article, we present a deconvolution software based on convex sets constructed from the phase...
A rank-constrained reformulation of the blind deconvolution problem on images taken with coherent il...
In image acquisition, the captured image is often the result of the object being convolved with a bl...
Cataloged from PDF version of article.Thesis (Ph.D.): Bilkent University, Department of Electrical a...
Image deconvolution is an ill-posed problem that requires a regularization term to solve. The most c...
[[abstract]]Blind image restoration is to recover the original images from the blurred images when t...
The total variation regularizer is well suited to piecewise smooth images. If we add the fact that t...
In this article we propose two minimization models for blind deconvolution. In the first model, we u...
In linear image restoration, the point spread function of the degrading system is assumed known even...
International audienceBlind image deconvolution recovers a deblurred image and the blur kernel from ...
Blurred image restoration poses a great challenge under the non-Gaussian noise environments in vario...
Image deblurring has long been modeled as a deconvolution problem. In the literature, the point-spre...
Abstract—In this article, two closed and convex sets for blind deconvolution problem are proposed. M...
The need for image restoration arises in many applications of various scientific disciplines, such a...
AbstractThe need for image restoration arises in many applications of various scientific disciplines...
In this article, we present a deconvolution software based on convex sets constructed from the phase...
A rank-constrained reformulation of the blind deconvolution problem on images taken with coherent il...
In image acquisition, the captured image is often the result of the object being convolved with a bl...
Cataloged from PDF version of article.Thesis (Ph.D.): Bilkent University, Department of Electrical a...
Image deconvolution is an ill-posed problem that requires a regularization term to solve. The most c...
[[abstract]]Blind image restoration is to recover the original images from the blurred images when t...
The total variation regularizer is well suited to piecewise smooth images. If we add the fact that t...
In this article we propose two minimization models for blind deconvolution. In the first model, we u...
In linear image restoration, the point spread function of the degrading system is assumed known even...
International audienceBlind image deconvolution recovers a deblurred image and the blur kernel from ...
Blurred image restoration poses a great challenge under the non-Gaussian noise environments in vario...
Image deblurring has long been modeled as a deconvolution problem. In the literature, the point-spre...