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Hyperspectral Python: HypPy
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This paper describes the design, implementation, and usage of a Python package called Hyperspectral Python (HypPy). Proprietary software for processing hyperspectral images is expensive, and tools developed using these packages cannot be freely distributed. The idea of HypPy is to be able to process hyperspectral images using free and open-source software. HypPy was developed using Python and relies on the array-processing capabilities of packages like NumPy and SciPy. HypPy was designed with practical imaging spectrometry in mind and has implemented a number of novel ideas. To name a few of these ideas, HypPy has BandMath and SpectralMath tools for processing images and spectra using Python statements, can process spectral libraries as if they were images, and can address bands by wavelength rather than band number. We expect HypPy to be beneficial for research, education, and projects using hyperspectral data because it is flexible and versatile.
Title: Hyperspectral Python: HypPy
Description:
This paper describes the design, implementation, and usage of a Python package called Hyperspectral Python (HypPy).
Proprietary software for processing hyperspectral images is expensive, and tools developed using these packages cannot be freely distributed.
The idea of HypPy is to be able to process hyperspectral images using free and open-source software.
HypPy was developed using Python and relies on the array-processing capabilities of packages like NumPy and SciPy.
HypPy was designed with practical imaging spectrometry in mind and has implemented a number of novel ideas.
To name a few of these ideas, HypPy has BandMath and SpectralMath tools for processing images and spectra using Python statements, can process spectral libraries as if they were images, and can address bands by wavelength rather than band number.
We expect HypPy to be beneficial for research, education, and projects using hyperspectral data because it is flexible and versatile.
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