Maybe. Perhaps its more like binning, with no need to demosaic. With sites that small you could have as many as 20 or 30 sites in the same physical area that a current sensel occupies. So you treat all of those sites as one pixel, derive the color from those and do not use any information from neighboring pixels to calculate the color?
I suppose you are thinking about how best to use the inherently tiny photodetectors of this diffraction splitting technology in a larger, "SLR sized" sensor by using the output of a cluster of these tiny photodetectors to produce each larger "super-pixel".
Maybe traditional demosaicing could be avoided, but there would still need to be some reconstruction of additive primaries from the mixed signals given by this approach, which are roughly "white plus red", "red", "white plus blue", and "blue".
From what I have heard, once you have to decode the primary colors using data from several photodetectors, it is best not to draw arbitrary boundaries between clusters of detectors grouped into bigger pixels, which leads to not using data from some nearby photodetectors just because they are on the wrong side of the line separating one pixel from the next. Instead it seems best in practice to do demosaicing with data from all sufficiently nearby sites, even going beyond immediate neighbors, though with greatest weight on the data from the nearest sites.
As an aside, there is overall all an excesive fear and disparagement of demosaicing and interpolation from people who do not know much about signal processing ... hence the excessive enthusiasm in some quarters for the Foveon X3 approach, with anti-interpolation extremists wielding their red-blue resolution test charts.