[GRASS-dev] [GSOC 2018] - Implement a series of image fusion algorithms in GRASS GIS

[Tudor-Emil COMAN (25633)]

Hi,


My name is Tudor-Emil Coman and I study Computer Science at the Faculty of
Automatic Control and Computer Science in Bucharest, Romania as a MSc student.

I'm currently researching geospatial image processing technologies and I have
primarly worked with Sentinel 2 data on numerous frameworks like ESA SNAP,
GDAL, GeoDjango, PostGIS and of course GRASS GIS.

I'm very interested in working this summer for a project I have seen proposed
on the GSOC 2018 idea page regarding the development of image fusion algorithms.
An already existing fusion algorithm is the High-Pass Filter Addition technique
implemented in the i.fusion.hpf module [1]. The scope of the project would be
to expand the capabilities of GRASS to combine data from different sensors.

The first algorithm I would implement is based on Nicolas Brodu's paper named
Super-resolving multiresolution images with band-independant geometry of
multispectral pixels [2]. The algorithm presented in this paper would increase
the resolution of certain low resolution bands by inferring some geometric
characteristics from high resolution bands. As opposed to the already existing
HPFA fusion method, this one does not require a panchromatic band making it
suitable for satellites that do not produce panchromatic bands.

I'm sure some other fusion algorithms are needed in GRASS-GIS that are not yet
implemented. I'm interested in suggestions about such algorithms so that I can
read about them and incorporate them into my final proposal.

[1] - https://grass.osgeo.org/grass74/manuals/addons/i.fusion.hpf.html
[2] - https://arxiv.org/abs/1609.07986

Cheers,
Tudor

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