A convex variational model for restoring SAR images corrupted by multiplicative noise
From MaRDI portal
Publication:778643
DOI10.1155/2020/1952782zbMath1459.94023OpenAlexW3035441921MaRDI QIDQ778643
Jian Lu, Jiachang Li, Hanmei Yang, Li-Xin Shen
Publication date: 3 July 2020
Published in: Mathematical Problems in Engineering (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1155/2020/1952782
Convex programming (90C25) Computing methodologies for image processing (68U10) Applications of optimal control and differential games (49N90) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
Related Items
Field of experts regularized nonlocal low rank matrix approximation for image denoising, Efficient Boosted DC Algorithm for Nonconvex Image Restoration with Rician Noise
Cites Work
- Unnamed Item
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Variational multiplicative noise removal by DC programming
- Multiplicative noise removal in imaging: an exp-model and its fixed-point proximity algorithm
- Fields of experts
- An algorithm for total variation minimization and applications
- A first-order primal-dual algorithm for convex problems with applications to imaging
- Data-driven tight frame construction and image denoising
- Simulation of linear and nonlinear advection-diffusion-reaction problems by a novel localized scheme
- Remote sensing images destriping using unidirectional hybrid total variation and nonconvex low-rank regularization
- Multiplicative noise removal with a sparsity-aware optimization model
- Superiorization of EM algorithm and its application in single-photon emission computed tomography (SPECT)
- Two-Level Convex Relaxed Variational Model for Multiplicative Denoising
- A Convex Variational Model for Restoring Blurred Images with Multiplicative Noise
- A New Convex Optimization Model for Multiplicative Noise and Blur Removal
- Proximity algorithms for image models: denoising
- A Nonlinear Inverse Scale Space Method for a Convex Multiplicative Noise Model
- A New Total Variation Method for Multiplicative Noise Removal
- The Split Bregman Method for L1-Regularized Problems
- A Variational Approach to Removing Multiplicative Noise
- The Convex Relaxation Method on Deconvolution Model withMultiplicative Noise
- Multiplicative Noise and Blur Removal by Framelet Decomposition and <inline-formula> <tex-math notation="LaTeX">$l_{1}$ </tex-math> </inline-formula>-Based L-Curve Method
- PCM-TV-TFV: A Novel Two-Stage Framework for Image Reconstruction from Fourier Data
- Computing Optical Flow via Variational Techniques
- Fast Gradient-Based Algorithms for Constrained Total Variation Image Denoising and Deblurring Problems
- Iterative Weighted Maximum Likelihood Denoising With Probabilistic Patch-Based Weights
- A New Multiplicative Denoising Variational Model Based on $m$th Root Transformation
- A Multiplicative Iterative Algorithm for Box-Constrained Penalized Likelihood Image Restoration
- Multiplicative Noise Removal via a Learned Dictionary
- Huber Fractal Image Coding Based on a Fitting Plane
- $ \newcommand{\e}{{\rm e}} \ell_{0}$ -minimization methods for image restoration problems based on wavelet frames
- Two-Step Approach for the Restoration of Images Corrupted by Multiplicative Noise