I have read Paul Rosens white paper on RTW shadow mapping many times but I have a hard time understanding how exactly the warp maps are converted from 1-D blurred importance maps to the 1-D warp maps. The source code is confusing to me aswell.
Key terms: Shadow map, warp maps, super cells, importance map, output frame.
The paper does not suggest the importance map resolution the demo uses, only that "resolution only needs to be large enough to detect the existence of the smallest features of interest" to shadow properly. It also states that "The warping maps are composed of a set of super-cells at equal or lower resolution than the base texture."
Is the importance map in the demo the same or lower resolution than the shadow map?
When collapsing the importance maps to 1-D, does it keep the same width (i.e 512x512 becomes 512)?
What resolution does the warp map have (looks like 28 super cells), does this mean that it is a 32 pixel long 1D texture?
How do you then collapse a 512px importance map down to a 32px warp map?
The warp map is colored red, blue and black. Is the Red channel displacing in the positive direction and blue displacing in the negative direction?
The "GetWarp(k)" formula to produce the 32 super cell values is kinda tricky to get the picture of. It sums upto the k'th super cell and divides by the total importance. Do we do this sum over the 512px importance map? Do we sum every 16 pixels in the 1-D importance map to create a super cell and divide by the total importance? Kinda hard to follow where and what we sum up.