Can someone enlighten me as to how a foundation model is better suited for visual geospatial data analysis (satellite images) versus an intelligently designed "filter?"
For example: you can easily use Photoshop to distinguish between various hues, apply a mask based on the selection, and then apply a color overlay, essentially "highlighting" a particular hue with another. (I imagine a similar approach can be used with hyperspectral imaging as well.)
As visual data is color-based, why can't such "dumb" filters be used? Why is this an AI challenge, let alone one well suited to the flexibility of foundation models?
*Edit: I believe I may have answered my own question. I assume the advantage this approach has is in the efficient bulk analysis of geospatial data. Platform consumes visual data, and spits out numerical data based on an analysis of the images. That numerical data can then be manipulated and fed into prediction models.