Hyperspectral Unmixing of Agricultural Images taken from UAV Using Adapted U-Net Architecture
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Abstract (arXiv)
The hyperspectral unmixing method is an algorithm that extracts material (usually called endmember) data from hyperspectral data cube pixels along with their abundances. Due to a lower spatial resolution of hyperspectral sensors data in each of the pixels may contain mixed information from multiple endmembers. In this paper we create a hyperspectral unmixing dataset, created from blueberry field data gathered by a hyperspectral camera mounted on a UAV. We also propose a hyperspectral unmixing algorithm based on U-Net network architecture to achieve more accurate unmixing results on existing and newly created hyperspectral unmixing datasets.
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References · 4
- 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
- 2022Deep Hyperspectral Unmixing using Transformer Networkcited by 22
- 2021A Latent Encoder Coupled Generative Adversarial Network (LE-GAN) for Efficient Hyperspectral Image Super-resolutioncited by 14
- 2023Deep Learning Techniques for Hyperspectral Image Analysis in Agriculture: A Reviewcited by 12
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