A supervised abundance estimation method for hyperspectral unmixing-Reference-Cited by-同舟云学术

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A supervised abundance estimation method for hyperspectral unmixing

Published:2018-01-26 Issue:4 Volume:9 Page:383-392
ISSN:2150-704X
Container-title:Remote Sensing Letters
language:en
Short-container-title:Remote Sensing Letters

Author:

Xu Xia¹²³,Shi Zhenwei¹²³,Pan Bin¹²³

Affiliation:

1. Image Processing Center, School of Astronautics, Beihang University, Beijing, China

2. Beijing Key Laboratory of Digital Media, Beihang University, Beijing, China

3. State Key Laboratory of Virtual Reality Technology and Systems, School of Astronautics, Beihang University, Beijing, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Beijing Municipality

Excellence Foundation of BUAA for PhD Students

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Earth and Planetary Sciences (miscellaneous)

Link

https://www.tandfonline.com/doi/pdf/10.1080/2150704X.2017.1415471

Reference16 articles.

1. Supervised Nonlinear Spectral Unmixing Using a Postnonlinear Mixing Model for Hyperspectral Imagery

2. Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches

3. PCANet: A Simple Deep Learning Baseline for Image Classification?

4. Approximation by superpositions of a sigmoidal function

5. Finding Structure in Time

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1. Hyperspectral Anomaly Detection Based on Spectral Similarity Variability Feature;Sensors;2024-08-30

2. Identification of Multiple Surface Water Contamination Sources Based on UV–Vis Spectral Unmixing with Turbidity Adaptiveness;ACS ES&T Water;2024-04-18

3. Hyperspectral image classification using a double-branch hierarchical partial convolution network;Remote Sensing Letters;2024-02-06

4. Pixel-to-Abundance Translation: Conditional Generative Adversarial Networks Based on Patch Transformer for Hyperspectral Unmixing;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

5. Beyond Pixel-Wise Unmixing: Spatial–Spectral Attention Fully Convolutional Networks for Abundance Estimation;Remote Sensing;2023-12-12

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