Description

homonim provides a command line interface and API for correcting remotely sensed imagery to approximate surface reflectance. It implements a form of spectral harmonisation, that adjusts for spatially varying atmospheric and anisotropic (BRDF) effects, by fusion with satellite surface reflectance data. Manual reflectance measurements and target placements are not required.

homonim is useful for pre-processing in quantitative mapping applications, and for reducing seamlines and other visual artefacts in image mosaics. It can be applied to multi-spectral drone, aerial and satellite imagery. The consistency of multi-temporal and multi-sensor data can improved through its use.

See the documentation site for more detail: https://homonim.readthedocs.io/.

Installation

homonim is available as a python 3 package, via pip or conda.

pip install homonim

conda install -c conda-forge homonim

Getting started

homonim --help

homonim <command> --help

homonim fuse source.tif reference.tif

homonim fuse -k 5 5 -m gain-blk-offset -od ./corrected source*.tif reference.tif

homonim compare source.tif corrected.tif reference.tif

from homonim import RasterFuse, Model

# urls of source and reference test images
src_file = (
    'https://raw.githubusercontent.com/leftfield-geospatial/homonim/main/'
    'tests/data/source/ngi_rgb_byte_1.tif'
)
ref_file = (
    'https://raw.githubusercontent.com/leftfield-geospatial/homonim/main/'
    'tests/data/reference/sentinel2_b432_byte.tif'
)

# path to corrected file to create
corr_file = './corrected.tif'

# Correct src_file to surface reflectance by fusion with ref_file, using the
# `gain-blk-offset` model and a kernel of 5 x 5 pixels.
with RasterFuse(src_file, ref_file) as fuse:
    fuse.process(corr_file, Model.gain_blk_offset, (5, 5), overwrite=True)

Usage

See the documentation here.

Terminology

homonim is shorthand for homogenise image and is a reference to the paper on which it is based.

Credits

homonim relies on these excellent packages:

• rasterio

• opencv

• numpy

License

homonim is licensed under the terms of the AGPLv3. This project is developed in collaboration with InnovUS at Stellenbosch University, alternative licenses can be arranged by contacting them.

Citation

Please cite use of the code as:

• Dugal Harris & Adriaan Van Niekerk (2019) Radiometric homogenisation of aerial images by calibrating with satellite data, International Journal of Remote Sensing, 40:7, 2623-2647, DOI: https://doi.org/10.1080/01431161.2018.1528404.

Bibtex:

@article{doi:10.1080/01431161.2018.1528404,
    author = {Dugal Harris and Adriaan Van Niekerk},
    title = {Radiometric homogenisation of aerial images by calibrating with satellite data},
    journal = {International Journal of Remote Sensing},
    volume = {40},
    number = {7},
    pages = {2623-2647},
    year  = {2019},
    publisher = {Taylor & Francis},
    doi = {10.1080/01431161.2018.1528404},
    URL = {https://doi.org/10.1080/01431161.2018.1528404},
}