Hyperspectral Unmixing of Agricultural Images taken from UAV Using Adapted U-Net Architecture

TL;DR

This paper introduces a new UAV-based hyperspectral dataset of blueberry fields and proposes a U-Net based algorithm for improved hyperspectral unmixing accuracy.

Contribution

It presents a novel hyperspectral unmixing dataset from UAV imagery and adapts U-Net architecture for enhanced unmixing performance.

Findings

Created a UAV hyperspectral dataset of blueberry fields

Proposed a U-Net based unmixing algorithm

Achieved more accurate unmixing results

Abstract

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.