Results 41 to 50 of about 35,627 (298)
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
doaj +1 more source
Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches [PDF]
, 2012 Imaging spectrometers measure electromagnetic energy scattered in their instantaneous field view in hundreds or thousands of spectral channels with higher spectral resolution than multispectral cameras.
Antonio Plaza +8 more
core +8 more sources
Remote Sensing, 2021 Hyperspectral imagery has been widely used in precision agriculture due to its rich spectral characteristics. With the rapid development of remote sensing technology, the airborne hyperspectral imagery shows detailed spatial information and temporal ...
Lifei Wei +7 more
doaj +1 more source
Semi-supervised linear spectral unmixing using a hierarchical Bayesian model for hyperspectral imagery [PDF]
, 2007 This paper proposes a hierarchical Bayesian model that can be used for semi-supervised hyperspectral image unmixing. The model assumes that the pixel reflectances result from linear combinations of pure component spectra contaminated by an additive ...
Chein-i Chang +4 more
core +6 more sources
Assessment of hydrogen fluoride damage to vegetation using optical remote sensing data [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013 This research assesses damage to vegetation from accidental gaseous hydrogen fluoride leakage, through the analysis of spectral features of the damaged plants using digital aerial photographs and airborne hyperspectral imagery.
C. U. Hyun, J. S. Lee, I. Lee
doaj +1 more source
Anomaly detection from hyperspectral imagery [PDF]
IEEE Signal Processing Magazine, 2002 We develop anomaly detectors, i.e., detectors that do not presuppose a signature model of one or more dimensions, for three clutter models: the local normal model, the global normal mixture model, and the global linear mixture model. The local normal model treats the neighborhood of a pixel as having a normal probability distribution.
D.W.J. Stein +5 more
openaire +1 more source
Compressive Hyperspectral Imaging Using Progressive Total Variation [PDF]
, 2014 Compressed Sensing (CS) is suitable for remote acquisition of hyperspectral images for earth observation, since it could exploit the strong spatial and spectral correlations, llowing to simplify the architecture of the onboard sensors. Solutions proposed
Barducci, Alessandro +4 more
core +2 more sources
Supervised nonlinear spectral unmixing using a post-nonlinear mixing model for hyperspectral imagery [PDF]
, 2011 This paper presents a nonlinear mixing model for hyperspectral image unmixing. The proposed model assumes that the pixel reflectances are nonlinear functions of pure spectral components contaminated by an additive white Gaussian noise.
Abderrahim Halimi +6 more
core +9 more sources
Remote Sensing, 2019 In this study, we automate tree species classification and mapping using field-based training data, high spatial resolution airborne hyperspectral imagery, and a convolutional neural network classifier (CNN).
Geoffrey A. Fricker +5 more
doaj +1 more source
Adaptive Markov random fields for joint unmixing and segmentation of hyperspectral image [PDF]
, 2013 Linear spectral unmixing is a challenging problem in hyperspectral imaging that consists of decomposing an observed pixel into a linear combination of pure spectra (or endmembers) with their corresponding proportions (or abundances). Endmember extraction
Benediktsson, Jon Atli +3 more
core +3 more sources