Relations Between Regularization and Diffusion Filtering
Journal of Mathematical Imaging and Vision
Segmentation of Pulmonary Nodule Images Using 1-Norm Minimization
Computational Optimization and Applications
An Algorithm for Total Variation Minimization and Applications
Journal of Mathematical Imaging and Vision
Adapted Total Variation for Artifact Free Decompression of JPEG Images
Journal of Mathematical Imaging and Vision
A Truncated Lagrange Method for Total Variation-Based Image Restoration
Journal of Mathematical Imaging and Vision
Video-to-video dynamic super-resolution for grayscale and color sequences
EURASIP Journal on Applied Signal Processing
A Nonlinear Multigrid Method for Total Variation Minimization from Image Restoration
Journal of Scientific Computing
An Algorithm for image removals and decompositions without inverse matrices
Journal of Computational and Applied Mathematics
A method based on rank-ordered filter to detect edges in cellular image
Pattern Recognition Letters
An Algorithm for Image Denoising with Automatic Noise Estimate
Journal of Mathematical Imaging and Vision
Efficient minimization method for a generalized total variation functional
IEEE Transactions on Image Processing
Differential geometry based solvation model I: Eulerian formulation
Journal of Computational Physics
A Multilevel Algorithm for Simultaneously Denoising and Deblurring Images
SIAM Journal on Scientific Computing
SIAM Journal on Scientific Computing
Approximate methods for constrained total variation minimization
CSR'06 Proceedings of the First international computer science conference on Theory and Applications
Constrained total variation minimization and application in computerized tomography
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Nonlinear multigrid method for solving the anisotropic image denoising models
Numerical Algorithms
Total variation regularization algorithms for images corrupted with different noise models: a review
Journal of Electrical and Computer Engineering
An Iterative Scheme for Total Variation-Based Image Denoising
Journal of Scientific Computing
A nonlinear level set model for image deblurring and denoising
The Visual Computer: International Journal of Computer Graphics
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A reliable and efficient computational algorithm for restoring blurred and noisy images is proposed. The restoration process is based on the minimal total variation principle introduced by Rudin et al. For discrete images, the proposed algorithm minimizes a piecewise linear l 1 function (a measure of total variation) subject to a single 2-norm inequality constraint (a measure of data fit). The algorithm starts by finding a feasible point for the inequality constraint using a (partial) conjugate gradient method. This corresponds to a deblurring process. Noise and other artifacts are removed by a subsequent total variation minimization process. The use of the linear l1 objective function for the total variation measurement leads to a simpler computational algorithm. Both the steepest descent and an affine scaling Newton method are considered to solve this constrained piecewise linear l1 minimization problem. The resulting algorithm, when viewed as an image restoration and enhancement process, has the feature that it can be used in an adaptive/interactive manner in situations when knowledge of the noise variance is either unavailable or unreliable. Numerical examples are presented to demonstrate the effectiveness of the proposed iterative image restoration and enhancement process