Poissonian image deconvolution via sparse and redundant representations and framelet regularization
DOI10.1155/2014/917040zbMath1407.94025OpenAlexW2040644190WikidataQ59070740 ScholiaQ59070740MaRDI QIDQ1719390
Yu Shi, Houzhang Fang, Guo-You Wang
Publication date: 8 February 2019
Published in: Mathematical Problems in Engineering (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1155/2014/917040
Numerical methods for wavelets (65T60) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Numerical methods for integral transforms (65R10) Numerical methods for inverse problems for integral equations (65R32)
Related Items (1)
Cites Work
- Affine systems in \(L_ 2(\mathbb{R}^d)\): The analysis of the analysis operator
- A Fast Total Variation Minimization Method for Image Restoration
- The Split Bregman Method for L1-Regularized Problems
- Split Bregman Methods and Frame Based Image Restoration
- Analysis K-SVD: A Dictionary-Learning Algorithm for the Analysis Sparse Model
- Analysis versus synthesis in signal priors
- Fast Image Recovery Using Variable Splitting and Constrained Optimization
- Restoration of Poissonian Images Using Alternating Direction Optimization
- Optimal Inversion of the Anscombe Transformation in Low-Count Poisson Image Denoising
- Framelet-Based Blind Motion Deblurring From a Single Image
- Sparse Poisson Noisy Image Deblurring
- Multiplicative Noise Removal via a Learned Dictionary
- Nonlocally Centralized Sparse Representation for Image Restoration
This page was built for publication: Poissonian image deconvolution via sparse and redundant representations and framelet regularization
