An efficient variational method for restoring images with combined additive and multiplicative noise
From MaRDI portal
Publication:1791810
DOI10.1007/s40819-016-0219-yzbMath1397.94012OpenAlexW2499683645MaRDI QIDQ1791810
Publication date: 11 October 2018
Published in: International Journal of Applied and Computational Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s40819-016-0219-y
synthetic aperture radar (SAR)fields of experts (FoE)fractional-order total variation (FOTV)Markov random fields (MRF)maximum a posteriori (MAP)
Random fields; image analysis (62M40) Image analysis in multivariate analysis (62H35) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
Related Items
A fractional analysis of Noyes-Field model for the nonlinear Belousov-Zhabotinsky reaction, A new collection of real world applications of fractional calculus in science and engineering, Exact solutions of the generalized multidimensional mathematical physics models via sub-equation method, q-homotopy analysis method for solving the seventh-order time-fractional Lax's Korteweg-de Vries and Sawada-Kotera equations, Efficient analytical techniques for solving time-fractional nonlinear coupled Jaulent-Miodek system with energy-dependent Schrödinger potential, A reliable solution of arbitrary order nonlinear Hunter-Saxton equation with time dependent derivative in Liouville-Caputo sense
Uses Software
Cites Work
- Nonlinear total variation based noise removal algorithms
- Fractional-order total variation image denoising based on proximity algorithm
- A class of fractional-order multi-scale variational models and alternating projection algorithm for image denoising
- Fields of experts
- Fractional differential approach to detecting textural features of digital image and its fractional differential filter implementation
- Removing multiplicative noise by Douglas-Rachford splitting methods
- Fractional-order total variation image restoration based on primal-dual algorithm
- A new variational model for removal of combined additive and multiplicative noise and a fast algorithm for its numerical approximation
- iPiano: Inertial Proximal Algorithm for Nonconvex Optimization
- A Nonlinear Inverse Scale Space Method for a Convex Multiplicative Noise Model
- A New Total Variation Method for Multiplicative Noise Removal
- A Variational Approach to Removing Multiplicative Noise
- Geometric Level Set Methods in Imaging, Vision, and Graphics
- Fractional Differential Mask: A Fractional Differential-Based Approach for Multiscale Texture Enhancement
