A fast image recovery algorithm based on splitting deblurring and denoising

作者：Deng, Liang-Jian; Guo, Huiqing; Huang, Ting-Zhu^*

来源：Journal of Computational and Applied Mathematics, 2015, 287: 88-97.

DOI：10.1016/j.cam.2015.03.035

• Image restoration
• Deblurring
• Denoising
• l(1) regularization
• Total-variation
• Shrinkage

In this paper, we employ a popular splitting strategy to design a fast iterative algorithm for image restoration. We divide the algorithm into two steps, i.e., deblurring step and denoising step. In the deblurring step, Fourier transform is employed for image deblurring under the periodic boundary condition. In the denoising step, we use a simple and fast method, called fast iterative shrinkage/thresholding algorithm (FISTA), to reduce image noise. In addition, we also give the convergence analysis for the proposed method. Visual and quantitative results demonstrate the proposed algorithm, applied to l(1) regularization model and total-variation (TV) regularization model, is a faster algorithm and keeps image details well.

• 出版日期2015-10-15
• 单位电子科技大学