Results 41 to 50 of about 1,165,369 (212)
Remote Sensing, 2016 Multiple endmember spectral mixture analysis (MESMA) has been widely applied for estimating fractional land covers from remote sensing imagery. MESMA has proven effective in addressing inter-class and intra-class endmember variability by allowing pixel ...
Yingbin Deng, Changshan Wu
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Remote Sensing, 2023 Spectral unmixing is one of the prime topics in hyperspectral image analysis, as images often contain multiple sources of spectra. Spectral variability is one of the key factors affecting unmixing accuracy, since spectral signatures are affected by ...
Ying Cheng +3 more
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Hyperspectral Unmixing with Gaussian Mixture Model and Low-Rank Representation
Remote Sensing, 2019 Gaussian mixture model (GMM) has been one of the most representative models for hyperspectral unmixing while considering endmember variability. However, the GMM unmixing models only have proper smoothness and sparsity prior constraints on the abundances ...
Yong Ma +6 more
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A Sparse Topic Relaxion and Group Clustering Model for Hyperspectral Unmixing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Hyperspectral unmixing (HU) has been a hot research topic in the field of hyperspectral remote sensing. In recent years, the employment of the probabilistic topic model to acquire the latent topics of hyperspectral images has been an effective method for
Qiqi Zhu +4 more
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Advanced Energy Materials, EarlyView.Light‐induced halide segregation limits the stability of mixed‐halide perovskites. This perspective shows how different mechanistic models can be viewed within a common free‐energy framework. It highlights the need to separate kinetic and thermodynamic aspects, the need for bulk‐sensitive measurements, and the need for controlled conditions to identify
Markus Griesbach +3 more
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Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Advanced Intelligent Discovery, EarlyView.Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
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Hyperspectral Unmixing with Gaussian Mixture Model and Spatial Group Sparsity
Remote Sensing, 2019 In recent years, endmember variability has received much attention in the field of hyperspectral unmixing. To solve the problem caused by the inaccuracy of the endmember signature, the endmembers are usually modeled to assume followed by a statistical ...
Qiwen Jin +7 more
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Remote Sensing, 2021 The accurate estimation of rice yield using remote sensing (RS) technology is crucially important for agricultural decision-making. The rice yield estimation model based on the vegetation index (VI) is commonly used when working with RS methods, however,
Ningge Yuan +7 more
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Geological Journal, EarlyView.Petrography, thermobarometry, and pseudosection modelling reveal peak metamorphic conditions of 3–7.5 kbar and 520°C–800°C in Tonian‐Cryogenian orthogneisses of the Dom Feliciano Belt. Metamorphic field gradients of 27°C/km–39°C/km and variable exhumation mechanisms support correlation of these units as remnants of a Himalayan‐type Piratini Orogeny ...
Thaiane Niederauer‐Santos +6 more
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, 2022 International audienceA hyperspectral image sequence can be obtained at different time in the same region from a hyperspectral sensor. The environmental change usually leads to variation in endmember reflectance, which has an important influence on ...
Lu, Youkang +5 more
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