Classification techniques for hyperspectral remote sensing [PDF]
, 2011 This study concerns with classification techniques in high dimensional space such as that of Hyperspectral Imaging (HSI) data sets, with objectives of understanding the strength and weakness of various classifiers and at the same time to study how ...
Kam, Firmin
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Illumination invariance and shadow compensation on hyperspectral images [PDF]
, 2014 To obtain intrinsic reflectance of the scene by hyperspectral imaging systems has been a scientific and engineering challenge. Factors such as illumination variations, atmospheric effects and viewing geometries are common artefacts which modulate the way
Ibrahim, Izzati
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Novel folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing [PDF]
, 2014 As a widely used approach for feature extraction and data reduction, Principal Components Analysis (PCA) suffers from high computational cost, large memory requirement and low efficacy in dealing with large dimensional datasets such as Hyperspectral ...
Han, Junwei +6 more
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Research and application of UAV-based hyperspectral remote sensing for smart city construction
Cognitive Robotics, 2022 Hyperspectral remote sensing has been an important technical means to obtain more refined information and provide rich, accurate, and reasonable data for the quantitative analysis and delicacy management of a ''smart city''.
Boxiong Yang +6 more
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Data in Brief, 2023 Maintaining rich biodiversity and being a habitat and resource for humans, tropical forests are one of the most important global biomes. These forest ecosystems have been experiencing a host of unregulated anthropogenic activities including illegal ...
C.B. Rajesh +4 more
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HYPERSPECTRAL TRANSFORMATION FROM EO-1 ALI IMAGERY USING PSEUDO-HYPERSPECTRAL IMAGE SYNTHESIS ALGORITHM [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 Hyperspectral remote sensing is more effective than multispectral remote sensing in many application fields because of having hundreds of observation bands with high spectral resolution.
N. T. Hoang, N. T. Hoang, K. Koike
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ISBDD Model for Classification of Hyperspectral Remote Sensing Imagery [PDF]
Sensors, 2018 The diverse density (DD) algorithm was proposed to handle the problem of low classification accuracy when training samples contain interference such as mixed pixels. The DD algorithm can learn a feature vector from training bags, which comprise instances (pixels).
Na Li 0014 +6 more
openaire +6 more sources
Improved sparse representation using adaptive spatial support for effective target detection in hyperspectral imagery [PDF]
, 2013 With increasing applications of hyperspectral imagery (HSI) in agriculture, mineralogy, military, and other fields, one of the fundamental tasks is accurate detection of the target of interest.
Li, Xiaohui +3 more
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Living up to the Hype of Hyperspectral Aquatic Remote Sensing: Science, Resources and Outlook
Frontiers in Environmental Science, 2021 Intensifying pressure on global aquatic resources and services due to population growth and climate change is inspiring new surveying technologies to provide science-based information in support of management and policy strategies.
Heidi M. Dierssen +6 more
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Remote Sensing, 2021 The chlorophyll-a (Chl-a) concentration of eutrophic lakes fluctuates significantly due to the disturbance of wind and anthropogenic activities on the water body. Consequently, estimation of the Chl-a concentration has become an immense challenge. Due to
Runfei Zhang +10 more
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