This repository contains the source code and supporting resources for iCalibrateImages, a desktop application for color calibration of RAW images using a ColorChecker reference target. It also includes a tutorial on how to capture images for calibration, as well as a random forest classifier for automatic classification of surface ice to derive fractional cryoconite cover.. The software and repository are part of a manuscript that will be submitted to a peer-reviewed journal.
Accurate color calibration is essential for field photography and image-based scientific analyses, particularly when images are acquired under varying lighting conditions or with different digital cameras. It enables users to standardize image colors, producing consistent and comparable outputs across cameras, sensors, and field campaigns.
The software provides an intuitive workflow that allows users to perform reliable color correction without requiring advanced expertise in image processing. It supports a wide range of digital cameras and RAW image formats, making it suitable for diverse field and laboratory applications.
Available for Windows, macOS, and Linux. Precompiled installation packages can be downloaded from the ERDA repository:
🔗 https://www.erda.au.dk/archives/b7374394d4a96cd79be717637ae7d11f/published-archive.html
The repository also includes sample images that demonstrate the calibration workflow and can be used to validate software performance. Just use the default installation options and it should work out of box. Note that there is a readme file for the macOS version that provides additional instructions for installation and ensure you follow the installation instructions to have the correct JAVA runtime. The starting up can be slow during installation or first time running. Please be patient.
A random forest classifier is available on ERDA to automatically classify the surface ice to derive the fractional cryoconite cover. Download the classifier and run src\applyClassifier.py to apply the classifier to the calibrated images. Then src\classification_analysis_two_classes.m can be used to analyze the classification results and derive the fractional cryoconite cover.
The results in the manuscript are derived from the calibrated images using the classifier and are available in stat\LAIs.xlsx. The script src\darkening_analysis.py is made to investigate the association between glacier algae, fractional cryoconite cover, and the darkening of the glacier surface. It can be used to reproduce the figures in the manuscript.
A tutorial on how to capture images for calibration is available in the doc\field_image_calibration_sample_tutorial.pdf. It provides detailed instructions on how to photograph the ColorChecker target under various lighting conditions and camera settings to ensure optimal calibration results.
If you use iCalibrateImages in your research, please cite the associated publication.
Shunan Feng (2026) “glacier-lab/Field-Image-Calibration: iCalibrateImages”. Zenodo. Available at: https://doi.org/10.5281/zenodo.21742413.Latex
@software{shunan_feng_2026_21742413,
author = {Shunan Feng},
title = {glacier-lab/Field-Image-Calibration:
iCalibrateImages
},
month = aug,
year = 2026,
publisher = {Zenodo},
version = {v1.1-beta},
doi = {10.5281/zenodo.21742413},
url = {https://doi.org/10.5281/zenodo.21742413},
}