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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