高光谱亚像元定位的线特征探测法

doi:10.11947/j.AGCS.2019.20180221

测绘学报 ›› 2019, Vol. 48 ›› Issue (11): 1464-1474.doi: 10.11947/j.AGCS.2019.20180221

• 摄影测量学与遥感 • 上一篇

高光谱亚像元定位的线特征探测法

刘照欣¹, 赵辽英¹, 厉小润², 陈淑涵²

1. 杭州电子科技大学计算机学院, 浙江杭州 310018;
2. 浙江大学电气工程学院, 浙江杭州 310027

收稿日期:2018-05-09 修回日期:2019-02-27 出版日期:2019-11-20 发布日期:2019-11-19
通讯作者: 厉小润 E-mail:lxr@zju.edu.cn
作者简介:刘照欣(1994-),女,硕士,研究方向为高光谱图像处理。E-mail:2272591726@qq.com
基金资助:
国家自然科学基金（61671408；61571170）；教育部联合基金（6141A02022350）；上海航天科技创新基金（SAST2016028）

Linear feature detection for hyperspectral subpixel mapping

LIU Zhaoxin¹, ZHAO Liaoying¹, LI Xiaorun², CHEN Shuhan²

1. School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China;
2. College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China

Received:2018-05-09 Revised:2019-02-27 Online:2019-11-20 Published:2019-11-19
Supported by:
The National Natural Science Foundation of China (Nos. 61671408;61571170);The Joint Fundation of the Ministry of Education of China(No. 6141A02022350);The Shanghai Aerospace Science and Technology Innovation Fund (No. SAST2016028)

摘要/Abstract

摘要： 未考虑地物亚像元级空间结构特征是影响高光谱亚像元定位精度的因素之一。为了有效解决这一问题，本文提出一种基于混合像元线特征探测的亚像元定位算法。首先，通过光谱解混确定含典型线状地物的混合像元。然后，基于完备直线集的最大线性指数方法确定其余含线特征的混合像元，使用模板匹配方法结合像元引力确定含线特征混合像元的亚像元类别。最后，基于线性优化的方法迭代确定剩余混合像元的亚像元类别。通过真实数据及仿真数据的试验，结果表明所提出的方法能有效提高亚像元定位精度。

关键词: 图像处理, 亚像元定位, 空间相关性, 线特征探测, 模板匹配

Abstract: The ignorance of the spatial structure of subpixel is one of the factors that influence the accuracy of hyperspectral subpixel mapping. In order to effectively solve this problem, a subpixel mapping algorithm is proposed that based on linear feature detection in mixed pixels. Firstly, the mixed pixels of typical linear feature classes are determined by spectral unmixing. Then, based on the maximum linear index method of the complete straight-line set, the linear features of remaining mixed pixels are determined. The template matching method is used in conjunction with the pixel attraction to determine the classes of linear subpixels. Finally, the subpixel categories of the remaining mixed pixels are iteratively determined based on the linear optimization method. The experimental results of real data and simulation data show that the proposed method can effectively improve the precision of subpixel mapping.

Key words: image processing, subpixel mapping, spatial correlation, linear feature detection, template matching

中图分类号:

P237

刘照欣, 赵辽英, 厉小润, 陈淑涵. 高光谱亚像元定位的线特征探测法[J]. 测绘学报, 2019, 48(11): 1464-1474.

LIU Zhaoxin, ZHAO Liaoying, LI Xiaorun, CHEN Shuhan. Linear feature detection for hyperspectral subpixel mapping[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(11): 1464-1474.

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高光谱亚像元定位的线特征探测法

Linear feature detection for hyperspectral subpixel mapping

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