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DOI

cross-sensor-cal

Python tool for cross-sensor calibration (This tool development is part of the NSF Award #DEB 2017889)

Macrosystems Disturbance Resilience - Sensor-convolution (4)

Python Scripts Description

  • neon2envi2.py

To convert neon data to envi format.

  • config_generator.py

To generate config files for topo and brdf corr.

  • image_correct.py

Which will load the config file and perform corrections

  • correction comparsion notebook

This file load config file and perfrom corrections and visualizes plots for before and after correction.

Steps to run the code:

  1. Convert neon data to envi.

    • CMD: python neon2envi2.py <path-to-dataset_name> <path-to-output_folder> -anc
    • Example: python neon2envi.py neon.h5 output/ -anc
    • Make sure output folder exists from the level at which the conversion code is being called.
    • You can change the name of the folder according to your preference.
  2. Generate config json

    • Edit the config_generator.py according what correction is to be performed.
    • This script has all the options required.
    • Run the script as python config_generator.py
    • This will create the config_.json in the folder specified in the config file.
  3. Perform Correction

    • Run the image_correct.py file with the config file as the cmd args
    • CMD: python image_correct.py <path-to-config-file>
    • Example: python image_correct.py output/config_01.json