Pyramid transform is a new sampling scheme. It is based on Shannon's sampling
theorem. Theoretically pyramid transform will not introduce error to the
dataset. After the pyramid transform, we get a frequency-dependent grid. This
new grid has a feature that
. This feature
makes the spatial prediction filter estimated in the pyramid domain
frequency-independent. We apply this new sampling scheme to signal/noise
separation. Our result shows that subsampling will not make the data more
unpredictable. The subsampled data is even more predictable than the
oversampled one. Pyramid scheme can eliminate low frequency noise, but it
also hurts the signal as well. We will continue this project and try to get
better results.