Feature extraction via 3-D homogeneous attribute decomposition for hyperspectral imagery classification

IF 3 3区 地球科学 Q2 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY International Journal of Remote Sensing Pub Date : 2024-09-10 DOI:10.1080/01431161.2024.2394234
Yong Zhang, Yishu Peng, Guoyun Zhang, Wujin Li
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Abstract

Feature extraction is a core aspect in hyperspectral image classification, which can extract key information closely related to ground cover from complex scene, thus improving classification accura...
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通过三维同质属性分解提取特征,用于高光谱图像分类
特征提取是高光谱图像分类的核心环节,它可以从复杂场景中提取与地表覆盖密切相关的关键信息,从而提高分类精度。
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来源期刊
International Journal of Remote Sensing
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).
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