Explore Laplacian eigenmaps for colourmap inference step

[kwinkunks]

Instead of trying to sparsify the graph of colours, possibly this dimensionality reduction step will work.

This paper uses Laplacian eigenmaps: https://ieeexplore.ieee.org/document/9395231 (GitHub: https://github.com/yuanlinping/deep_colormap_extraction)

They are following the recipe in here: https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.12567

Some Python resources on the topic:

• https://juanitorduz.github.io/laplacian_eigenmaps_dim_red/
• https://github.com/JAVI897/Laplacian-Eigenmaps
• https://pythonawesome.com/fast-laplacian-eigenmaps-lightweight-multicore-le-for-non-linear-dimensional-reduction-with-minimal-memory-usage/