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Analysis of Hyperspectral Data to Develop an Approach for Document Images [PDF]
Sensors, 2023 Hyperspectral data analysis is being utilized as an effective and compelling tool for image processing, providing unprecedented levels of information and insights for various applications.
Zainab Zaman +2 more
doaj +2 more sources
Principal component analysis of hyperspectral data for early detection of mould in cheeselets. [PDF]
Curr Res Food Sci, 2021 The application of non-destructive process analytical technologies in the area of food science got a lot of attention the past years. In this work we used hyperspectral imaging to detect mould on milk agar and cheese.
Farrugia J +4 more
europepmc +2 more sources
An Overview on Linear Unmixing of Hyperspectral Data [PDF]
Mathematical Problems in Engineering, 2020 Hyperspectral remote sensing technology has a strong capability for ground object detection due to the low spatial resolution of hyperspectral imaging spectrometers. A single pixel that leads to a hyperspectral remote sensing image usually contains more than one feature coverage type, resulting in a mixed pixel.
Jiaojiao Wei, Xiaofei Wang
openaire +2 more sources
GIScience & Remote Sensing, 2023 Recent growth in unmanned aerial vehicle (UAV) technology have promoted the detailed mapping of individual tree species. However, the in-depth mining and comprehending of the significance of features derived from high-resolution UAV data for tree species
Ying Quan +4 more
semanticscholar +1 more source
DIMENSIONALITY REDUCTION VIA AN ORTHOGONAL AUTOENCODER APPROACH FOR HYPERSPECTRAL IMAGE CLASSIFICATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Nowadays, the increasing amount of information provided by hyperspectral sensors requires optimal solutions to ease the subsequent analysis of the produced data.
V. H. Ayma, V. A. Ayma, J. Gutierrez
doaj +1 more source
Journal of Experimental Botany, 2021 Partial least squares regression (PLSR) modelling is a statistical technique for correlating datasets, and involves the fitting of a linear regression between two matrices.
A. C. Burnett +9 more
semanticscholar +1 more source
Editorial for Special Issue “Advances in Hyperspectral Data Exploitation”
Remote Sensing, 2022 Hyperspectral imaging (HSI) has emerged as a promising, advanced technology in remote sensing and has demonstrated great potential in the exploitation of a wide variety of data.
Chein-I Chang +8 more
doaj +1 more source
Remote Sensing, 2022 Using unmanned aerial vehicle (UAV) hyperspectral images to accurately estimate the chlorophyll content of summer maize is of great significance for crop growth monitoring, fertilizer management, and the development of precision agriculture ...
Bilige Sudu +7 more
semanticscholar +1 more source
Spectral Variability in Hyperspectral Data Unmixing: A comprehensive review [PDF]
IEEE Geoscience and Remote Sensing Magazine, 2020 The spectral signatures of the materials contained in hyperspectral images, also called endmembers (EMs), can be significantly affected by variations in atmospheric, illumination, and environmental conditions that typically occur within an image ...
R. Borsoi +8 more
semanticscholar +1 more source
Remote Sensing, 2023 Hyperspectral data usually consists of hundreds of narrow spectral bands and provides more detailed spectral characteristics compared to commonly used multispectral data in remote sensing applications.
Hua Yang +5 more
doaj +1 more source