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A Geographic Information-Assisted Temporal Mixture Analysis for Addressing the Issue of Endmember Class and Endmember Spectra Variability [PDF]
Sensors, 2017 Spectral mixture analysis (SMA) is a common approach for parameterizing biophysical fractions of urban environment and widely applied in many fields. For successful SMA, the selection of endmember class and corresponding spectra has been assumed as the ...
Changshan Wu, Wenliang Li
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Remote Sensing, 2021 With the improvement of spatial resolution of hyperspectral remote sensing images, the influence of spectral variability is gradually appearing in hyperspectral unmixing.
Bo Du, Shanwei Liu, Mingming Xu
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Hyperspectral Unmixing With Endmember Variability via Alternating Angle Minimization [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2016 In hyperspectral unmixing applications, one typically assumes that a single spectrum exists for every endmember. In many scenarios, this is not the case, and one requires a set or a distribution of spectra to represent an endmember or class. This inherent spectral variability can pose severe difficulties in classical unmixing approaches. In this paper,
Paul Gader, Alina Zare, Rob Heylen
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A Hierarchical Sparsity Unmixing Method to Address Endmember Variability in Hyperspectral Image [PDF]
Remote Sensing, 2018 With a low spectral resolution hyperspectral sensor, the signal recorded from a given pixel against the complex background is a mixture of spectral contents. To improve the accuracy of classification and subpixel object detection, hyperspectral unmixing (
Yang Shao, Jinhui Lan, Jinlin Zou
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The AMEE-PPI Method to Extract Typical Outcrop Endmembers from GF-5 Hyperspectral Images [PDF]
SensorsMixed pixels remain a central obstacle to reliable endmember extraction from hyperspectral imagery. We present AMEE–PPI, a hybrid method that embeds the Pure Pixel Index (PPI) within morphological structuring elements and propagates spectral purity via ...
Lin Hu +6 more
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Remote Sensing, 2015 As an important indicator of anthropogenic impacts on the Earth’s surface, it is of great necessity to accurately map large-scale urbanized areas for various science and policy applications.
Chengbin Deng
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Source Apportionment of Heavy Metals in Stream Sediments from the Hilly Western Wanda Mountains Based on PCA-APCS-MLR [PDF]
ToxicsThe hilly terrain at the western foot of the Wanda Mountains boasts intricate geological conditions, compounded by long-term mineral extraction and farming activities.
Xiangjin Yan +5 more
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A Gaussian Mixture Model Representation of Endmember Variability in Hyperspectral Unmixing
IEEE Transactions on Image Processing, 2018 Hyperspectral unmixing while considering endmember variability is usually performed by the normal compositional model (NCM), where the endmembers for each pixel are assumed to be sampled from unimodal Gaussian distributions. However, in real applications, the distribution of a material is often not Gaussian.
Anand Rangarajan, Yuan Zhou
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GIScience and Remote SensingTemporal unmixing, an extension of traditional spectral unmixing in a multi-temporal context, leverages endmembers defined by their temporal signatures to decompose mixed pixel responses into fractional cover.
Da Zhang, Chen Shi
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Reducing the Effect of the Endmembers’ Spectral Variability by Selecting the Optimal Spectral Bands [PDF]
Remote Sensing, 2017 Variable environmental conditions cause different spectral responses of scene endmembers. Ignoring these variations affects the accuracy of fractional abundances obtained from linear spectral unmixing. On the other hand, the correlation between the bands
Omid Ghaffari +2 more
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