| 基于线性解混的高光谱图像目标检测研究 |
| |
| 引用本文： | 杨桄,田张男,李豪,关世豪.基于线性解混的高光谱图像目标检测研究[J].激光技术,2020,44(2):143-147. |
| |
| 作者姓名： | 杨桄 田张男 李豪 关世豪 |
| |
| 作者单位： | 空军航空大学，长春 130022 |
| |
| 基金项目： | 吉林省科技发展计划资助项目 |
| |
| 摘 要： | 高光谱图像的空间分辨率普遍较低，导致混合像元大量存在，为目标检测带来了一定困难。为了实现复杂背景下的高光谱图像目标检测，提出了一种去端元的目标检测方法。在光谱解混技术的基础上，建立了复杂背景下的光谱混合模型并加以改进，采用多次去端元的方法，取得了简化背景之后的高光谱图像。结果表明，与传统的RX目标检测算法相比，所提出的算法能够显著提升目标检测效果。在实际的军事运用中，为大尺幅图像的目标识别和揭露伪装提供了思路。
|
| 关 键 词： | 光谱学 高光谱图像 去除端元 目标检测 |
| 收稿时间： | 2019-05-22 |
Research of target detection of hyperspectral images in complex background based on linear unmixing |
| |
| Abstract: | The spatial resolution of hyperspectral images was generally low. As a result, a large number of mixed pixels existed. It brought some difficulties to target detection. In order to realize target detection in hyperspectral images under complex background, a target detection method based on de-endmember was proposed. On the basis of spectral de-mixing technology, the spectral mixing model under complex background was established and improved. The method of removing endpoints many times was adopted. The hyperspectral image after simplified background was obtained. The results show that, compared with the traditional RX target detection algorithm, the proposed algorithm can significantly improve the performance of target detection. In practical military applications, it provides a train of thought for target recognition and camouflage exposure of large-scale images. |
| |
| Keywords: | |
| 本文献已被 万方数据 等数据库收录！ |
| 点击此处可从《激光技术》浏览原始摘要信息 |
|
点击此处可从《激光技术》下载全文 |
|
