Hyperspectral anomaly detection based on adaptive background dictionary construction and collaborative representation

IF 3 3区地球科学 Q2 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY

International Journal of Remote Sensing Pub Date : 2024-05-07 DOI:10.1080/01431161.2024.2343431

Mingming Xu, Jinhao Zhang, Shanwei Liu, Hui Sheng

引用次数: 0

Abstract

Collaborative representation-based (CR) methods have received widespread attention in hyperspectral anomaly detection, but the results are greatly affected by the quality of the background dictiona...

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基于自适应背景字典构建和协作表示的高光谱异常检测

在高光谱异常检测中，基于协作表示（CR）的方法受到广泛关注，但其结果在很大程度上受到背景辞典质量的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Remote Sensing 工程技术-成像科学与照相技术

CiteScore

7.00

自引率

5.90%

发文量

219

审稿时长

4.8 months

期刊介绍： The International Journal of Remote Sensing ( IJRS) is concerned with the theory, science and technology of remote sensing and novel applications of remotely sensed data. The journal’s focus includes remote sensing of the atmosphere, biosphere, cryosphere and the terrestrial earth, as well as human modifications to the earth system. Principal topics include: • Remotely sensed data collection, analysis, interpretation and display. • Surveying from space, air, water and ground platforms. • Imaging and related sensors. • Image processing. • Use of remotely sensed data. • Economic surveys and cost-benefit analyses. • Drones Section: Remote sensing with unmanned aerial systems (UASs, also known as unmanned aerial vehicles (UAVs), or drones).