Traditional imagery—provided, for example, by RGB and/or NIR sensors—has proven to be
useful in many agroforestry applications. However, it lacks the spectral range and precision …

Fighting Earth's degradation and safeguarding the environment are subjects of topical
interest and sources of hot debate in today's society. According to the United Nations, there …

Hyperspectral imagery can obtain hundreds of narrow spectral bands of ground objects. The
abundant and detailed spectral information offers a unique diagnostic identification ability for …

Deep learning has gained popularity in a variety of computer vision tasks. Recently, it has
also been successfully applied for hyperspectral image classification tasks. Training deep …

Anomaly detection of hyperspectral data has been gaining particular attention for its ability in
detecting targets in an unsupervised manner. Autoencoder (AE), together with its variants …

Hyperspectral remote sensing technology has advanced significantly in the past two
decades. Current sensors onboard airborne and spaceborne platforms cover large areas of …

Anomaly detection has become an important remote sensing application due to the
abundant spectral and spatial information contained in hyperspectral images. Recently …

Anomaly detection is playing an increasingly important role in hyperspectral image (HSI)
processing. The traditional anomaly detection methods mainly extract knowledge from the …

Over the last decade, hyperspectral imagery (HSI) obtained by remote sensing systems has
provided significant information about the spectral characteristics of the materials in the …

高光谱遥感是对地观测的重要手段, 高光谱图像处理与信息提取技术则是高光谱遥感领域的核心
研究内容之一. 本文简要介绍了高光谱遥感的主要特点, 系统梳理了高光谱图像处理与信息提取 …