Advances in hyperspectral image and signal processing: A comprehensive overview of the state of the art
Recent advances in airborne and spaceborne hyperspectral imaging technology have
provided end users with rich spectral, spatial, and temporal information. They have made a …
provided end users with rich spectral, spatial, and temporal information. They have made a …
Hyperspectral imaging technology for quality and safety evaluation of horticultural products: A review and celebration of the past 20-year progress
In the past 20 years, hyperspectral imaging has been widely investigated as an emerging,
promising technology for evaluating quality and safety of horticultural products. This …
promising technology for evaluating quality and safety of horticultural products. This …
Hyperspectral remote sensing data analysis and future challenges
JM Bioucas-Dias, A Plaza… - … and remote sensing …, 2013 - ieeexplore.ieee.org
Hyperspectral remote sensing technology has advanced significantly in the past two
decades. Current sensors onboard airborne and spaceborne platforms cover large areas of …
decades. Current sensors onboard airborne and spaceborne platforms cover large areas of …
高光谱图像处理与信息提取前沿.
张兵 - Journal of Remote Sensing, 2016 - search.ebscohost.com
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 …
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 …
[HTML][HTML] Advances in Earth observation and machine learning for quantifying blue carbon
Blue carbon ecosystems (mangroves, seagrasses and saltmarshes) are highly productive
coastal habitats, and are considered some of the most carbon-dense ecosystems on the …
coastal habitats, and are considered some of the most carbon-dense ecosystems on the …
Real-time progressive hyperspectral image processing
CI Chang - Cham, Switzerland: Springer, 2016 - Springer
Because of recent advances of hyperspectral imaging technology with hundreds of spectral
bands being used for data acquisition, how to handle enormous data volumes using …
bands being used for data acquisition, how to handle enormous data volumes using …
A new GPU implementation of support vector machines for fast hyperspectral image classification
The storage and processing of remotely sensed hyperspectral images (HSIs) is facing
important challenges due to the computational requirements involved in the analysis of …
important challenges due to the computational requirements involved in the analysis of …
Cloud-based analysis of large-scale hyperspectral imagery for oil spill detection
JM Haut, S Moreno-Alvarez… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Spectral indices are of fundamental importance in providing insights into the distinctive
characteristics of oil spills, making them indispensable tools for effective action planning …
characteristics of oil spills, making them indispensable tools for effective action planning …
Enhanced spatial–temporal Savitzky–Golay method for reconstructing high-quality NDVI time series: Reduced sensitivity to quality flags and improved computational …
The spatial–temporal Savitzky–Golay (STSG) method for noise reduction can address the
problem of tempor-ally continuous normalized difference vegetation index (NDVI) gaps and …
problem of tempor-ally continuous normalized difference vegetation index (NDVI) gaps and …
Hyperspectral unmixing on GPUs and multi-core processors: A comparison
One of the main problems in the analysis of remotely sensed hyperspectral data cubes is the
presence of mixed pixels, which arise when the spatial resolution of the sensor is not able to …
presence of mixed pixels, which arise when the spatial resolution of the sensor is not able to …