数字技术与应用Issue(12)：72-74,3.
基于权值核范数最小化的红外背景杂波抑制
司马端 1安玮 1王普 1龙云利1
作者信息
- 1. 国防科技大学电子科学与工程学院湖南长沙 410073
- 折叠
摘要
Abstract
An algorithm of spatial background clutter suppression of infrared image based on weighted nuclear norm minimization theory is proposed for smal target detection in complicated background. Firstly,by exploiting the image nonlocal self-similarity,the nonlocal self-similar image patch vectors are stacked into a low rank matrix.Then, the singular values of low rank matrix are assigned different weights.Finaly, by using weighted nuclear norm minimization converting it to an optimization problem. While the data fidelity to observed image holds, the background estimate can stil maintain edges, effectively reducing false-alarm where gray level varies dramaticaly in complicated background. Feasibility and effectiveness of the algorithm is verified by simulation experiments. Analysis of the result shows that background suppression performance is remarkably improved compared to traditional method.关键词
非局部相似/加权核范数/背景抑制/红外小目标Key words
Nonlocal self-similarity/Weighted nuclear norm/Background suppression/Infrared smal target分类
信息技术与安全科学引用本文复制引用
司马端,安玮,王普,龙云利..基于权值核范数最小化的红外背景杂波抑制[J].数字技术与应用,2015,(12):72-74,3.
