SKIP to Questions below if you want :
In super resolution I can create a high resolution signal from a low resolution signal. But it is also possible that the low resolution signal contains aliasing. The problem with aliasing is that it cannot be distinguished between the real low resolution frequencies. But in super resolution you can make multiple low resolution measurements with aliasing and calculate the shift between the signals (afaik) that can help to reconstruct a higher resolution signal. Check some papers like here : Multi-Frame super resolution, SR from aliased images
What I am thinking is if I can make multiple shots from one scene with aliasing and construct a higher resolution image out of it, how could I apply this to vibration from a machine. In the first paper google shows how they use the vibrations from a hand for taking multiple photos from one scene. The vibrations from a human hand help to capture different frequencies with aliasing. Later on, all merged can be used for super-resolution.
- I have a fixed sensor on a machine which basically means I have a camera fixed on a stand(compare photo camera wich takes multiple pictures at same time from the same scene with aliasing to construct a higher resolution). How would this affect the super-resolution in comparison to using different angles in parallel to have multiple measurements with different offsets?
- Could I apply this on vibration with making a long measurement, dividing the measurement in different blocks and trying to merge them as they where different captures, instead of using different angles?