/spectral-similarity-metrics-comparison

Code for the paper An analysis of spectral similarity measures

Primary LanguagePythonBSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

An analysis of spectral similarity measures

Code for the paper An analysis of spectral similarity measures. In the paper the most used measures for the assessment of spectral similarity are analyzed. Please read the paper for details.

Dependencies

  • Python 3.9
  • numpy
  • scikit-image

In order to successfully run the code, install the packages listed in requirements.txt as follows:

pip install -r requirements.txt

Citation

If you use our code, please consider cite the following:

  • Mirko Agarla, Simone Bianco, Luigi Celona, Raimondo Schettini, and Mikhail Tchobanou. An analysis of spectral similarity measures. In Color and Imaging Conference, volume 2021, Society for Imaging Science and Technology, volume 2021, number 6, pp. 300-305, 2021.
@inproceedings{agarla2021spectralmeasures,
 author = {Agarla, Mirko and Bianco, Simone and Celona, Luigi and Schettini, Raimondo and Tchobanou, Mikhail},
 year = {2021},
 title = {An analysis of spectral similarity measures},
 organization = {Society for Imaging Science and Technology},
 booktitle = {Color and Imaging Conference},
 volume = {2021},
 number = {6},
 doi = {https://doi.org/10.2352/issn.2169-2629.2021.29.300},
 pages = {300--305},
}

Available measures

Mean error measures

Similarity measures

Angular measures

Colorimetric error measures

Other measures

Acknowledgement

This research was supported by Huawei Technologies Co. Ltd. Russia.