电子学报2017，Vol.45Issue(1)：181-191,11.DOI:10.3969/j.issn.0372-2112.2017.01.025
欧拉弹性正则化的图像泊松去噪
Image Poisson Denoising Based on Euler's Elastica Regularization
摘要
Abstract
Poisson noise has strong relationship with the gray-values of image,meanwhile the gray-values of image can be represented by level line.In the framework of the Bayesian-MAP,a Poisson denoising variational regularization model is proposed.The Euler's elastica energy is used as a prior regularization term combined with negative-log Poisson likelihood.By using the alternating direction method of multipliers (ADMM),we transform the original high-order optimization problem into several low-order sub-problems.Then the lagged diffusivity fixed point iteration is applied to solve the high-order nonlinear term.For images with strong or weak Poisson noise,experiments show the validity and efficiency of the proposed method both in preserving geometric structure and suppressing noise.关键词
泊松去噪/欧拉弹性/水平集/变分正则化Key words
Poisson denoising/Euler's elastica/level line/variational regularization分类
信息技术与安全科学引用本文复制引用
张峥嵘,刘红毅,韦志辉..欧拉弹性正则化的图像泊松去噪[J].电子学报,2017,45(1):181-191,11.基金项目
国家自然科学基金(No.61301215,No.61471199) （No.61301215,No.61471199）
国家自然科学重点基金(No.11431015) （No.11431015）
