A Fast and Effective Algorithm for a Poisson Denoising Model With Total Variation

In this letter, we present a fast and effective algorithm for solving the Poisson-modified total variation model proposed in [Le et al., "A variational approach to reconstructing images corrupted by Poisson noise," J. Math. Imag. Vis., vol. 27, no 3, pp. 257-263, Apr. 2007]. The existence...

Full description

Saved in:
Bibliographic Details
Published in:IEEE signal processing letters 2017-03, Vol.24 (3), p.269-273
Main Authors: Wang, Wei, He, Chuanjiang
Format: Article
Language:English
Subjects:
Extraterrestrial measurements
Gradient descent
Mathematical model
Noise measurement
Noise reduction
Numerical models
Photonics
Poisson denoising
semi-implicit scheme
Signal processing algorithms
total variation
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this letter, we present a fast and effective algorithm for solving the Poisson-modified total variation model proposed in [Le et al., "A variational approach to reconstructing images corrupted by Poisson noise," J. Math. Imag. Vis., vol. 27, no 3, pp. 257-263, Apr. 2007]. The existence and uniqueness of solution for the model are proved by using a different method. A semi-implicit difference scheme is designed to discretize the derived gradient descent flow with a large time step. Different from the original numerical scheme, our scheme is conditional stable with a less stringent condition and can ensure that the numerical solution is strictly positive in image domain. Experimental results show the efficiency and effectiveness of our algorithm.
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2017.2654480