[1]毕晓君,周泽宇.基于大规模多目标优化的高光谱稀疏解混算法[J].哈尔滨工程大学学报,2019,40(07):1354-1360.[doi:10.11990/jheu.201807075]
 BI Xiaojun,ZHOU Zeyu.Sparse unmixing of hyperspectral images based on large-scale many-objective optimization algorithm[J].hebgcdxxb,2019,40(07):1354-1360.[doi:10.11990/jheu.201807075]
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基于大规模多目标优化的高光谱稀疏解混算法(/HTML)
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《哈尔滨工程大学学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
40
期数:
2019年07期
页码:
1354-1360
栏目:
出版日期:
2019-07-05

文章信息/Info

Title:
Sparse unmixing of hyperspectral images based on large-scale many-objective optimization algorithm
作者:
毕晓君1 周泽宇2
1. 中央民族大学 信息工程学院, 北京 100081;
2. 哈尔滨工程大学 信息与通信工程学院, 黑龙江 哈尔滨 150001
Author(s):
BI Xiaojun1 ZHOU Zeyu2
1. School of Information Engineering, Minzu University of China, Beijing 100081, China;
2. Department of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
关键词:
高光谱图像线性光谱解混模型稀疏解混多目标优化大规模多目标优化算法拐点区域
分类号:
TP751.1
DOI:
10.11990/jheu.201807075
文献标志码:
A
摘要:
针对现有多目标稀疏解混算法中存在因随机分组策略的不足和拐点选择具有单一性,进而导致高光谱数据解混精度不高的问题,本文提出一种基于大规模多目标优化的高光谱稀疏解混算法。引入大规模多目标优化算法的决策变量分组策略,并提出有约束拐点区域选择策略求取丰度最优解,进而提高解混精度。对模拟和真实的高光谱数据进行实验,结果表明:本文算法在解混精度上有大幅度提升,与其他算法比较,可以看出本文算法得到的丰度图边缘细节处理得更好,抗噪性能更强,验证了本文提出算法的有效性和先进性。

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2018-07-19。
基金项目:国家自然科学基金项目(51779050).
作者简介:毕晓君,女,教授,博士生导师;周泽宇,女,硕士.
通讯作者:周泽宇,E-mail:zhouzeyu100@hrbeu.edu.cn
更新日期/Last Update: 2019-07-04