I am trying to understand the LidarBoost algorithm as explained in this paper (PDF warning).
I don't understand how they take the original depth-images $Y_k$ and transform them into the up-sampled images $D_k$. I get how optical flow is used to align the $Y_k$ into a chosen reference frame, but is the transform between $Y_k$ and $D_k$ just a standard image up-sampling with nearest neighbors for the "interpolation" step? If that's the case, can someone explain how they get the term $W_k$ in their data term of the energy function? They say this about it, but I don't understand how to construct $W_k$ for each $k$:
$W_k \in \mathbb{R}^{\beta_n \times \beta_m}$ is a banded matrix that encodes the positions of $D_k$ which one samples from during resampling on the high-resolution target grid
I'm trying (so far frustratingly ineffectively) to get enough of a sense of the algorithm to try to implement it.