hyperquest: A Python package for estimating image-wide quality estimation metrics of hyperspectral imaging (imaging spectroscopy). Computations are sped up and scale with number of cpus. Available methods and summaries can be found in documentation.
- Data must be in NetCDF (.nc) or ENVI (.hdr)
- Currently data is expected in Radiance.
- For smile & striping methods, data must not be georeferenced (typically referred to as L1B before ortho)
- Pushbroom imaging spectrometer, such as, but not limited to:
- AVIRIS-NG, AVIRIS-3, DESIS, EnMAP, EMIT, GaoFen-5, HISUI, Hyperion EO-1, HySIS, PRISMA, Tanager-1
NOTE: this is under active development. It is important to note that noise methods shown here do not account for spectrally correlated noise. This is a work in progress as I digest literature and translate into python.
The latest release can be installed via pip:
pip install hyperquestIf using Windows PC, you must have "Build Tools" installed to compile cython code,
- Testing on my beat-up Windows PC (Windows11), I did the following to get it to work
- Installed Visual Studio Build Tools 2022
- making sure to check the box next to "Desktop development with C++"
- and then, pip install hyperquest
- see EMIT example which has different methods computed over Libya-4.
- Can be installed on Unix type system using the following link:
Brent Wilder. (2025). brentwilder/HyperQuest: v0.XXX (vXXX). Zenodo. https://doi.org/10.5281/zenodo.14890171