Image Estimation Using Doubly Stochastic Gaussian Random Field Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
On Advances in Statistical Modeling of Natural Images
Journal of Mathematical Imaging and Vision
On the Hierarchical Bayesian Approach to Image Restoration: Applications to Astronomical Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Algorithm for Total Variation Minimization and Applications
Journal of Mathematical Imaging and Vision
A Non-Local Algorithm for Image Denoising
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Nonlocal Prior Bayesian Tomographic Reconstruction
Journal of Mathematical Imaging and Vision
Robust 3D Face Recognition by Local Shape Difference Boosting
IEEE Transactions on Pattern Analysis and Machine Intelligence
ForWaRD: Fourier-wavelet regularized deconvolution for ill-conditioned systems
IEEE Transactions on Signal Processing
A unified approach to statistical tomography using coordinate descent optimization
IEEE Transactions on Image Processing
Adaptively regularized constrained total least-squares image restoration
IEEE Transactions on Image Processing
Image recovery using partitioned-separable paraboloidal surrogate coordinate ascent algorithms
IEEE Transactions on Image Processing
An EM algorithm for wavelet-based image restoration
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
A segmentation-based regularization term for image deconvolution
IEEE Transactions on Image Processing
Bayesian Restoration Using a New Nonstationary Edge-Preserving Image Prior
IEEE Transactions on Image Processing
A New TwIST: Two-Step Iterative Shrinkage/Thresholding Algorithms for Image Restoration
IEEE Transactions on Image Processing
On some Bayesian/regularization methods for image restoration
IEEE Transactions on Image Processing
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Bayesian or Maximum a posteriori (MAP) approaches can effectively overcome the ill-posed problems of image restoration or deconvolution through incorporating a priori image information. Many restoration methods, such as nonquadratic prior Bayesian restoration and total variation regularization, have been proposed with edge-preserving and noise-removing properties. However, these methods are often inefficient in restoring continuous variation region and suppressing block artifacts. To handle this, this paper proposes a Bayesian restoration approach with a novel spatial adaptive (SA) prior. Through selectively and adaptively incorporating the nonlocal image information into the SA prior model, the proposed method effectively suppress the negative disturbance from irrelevant neighbor pixels, and utilizes the positive regularization from the relevant ones. A twostep restoration algorithm for the proposed approach is also given. Comparative experimentation and analysis demonstrate that, bearing high-quality edge-preserving and noise-removing properties, the proposed restoration also has good deblocking property.