It only matters if you need physically accurate data - ie if your brain can't process the multi path error and correct for it. A bat sees in multi path error an

It only matters if you need physically accurate data - ie if your brain can't process the multi path error and correct for it. A bat sees in multi path error and has no problem with it. I assume a machine vision system can learn to perform with multipath error and indirectly account for it. ie, it sees an apple with multipath error, and still knows it's an Apple. There are options to fix multipath and recover the underlying ground truth 1) you can do a reverse raytrace and iteratively correct for the error - somewhat expensive, but there's tricks and shortcuts to accelerate 2) hardware fix to measure the multipath component separately and subtract / correct it - there's several ways to do this - there are some patents on it that I've worked on. The same methods also can remove background signal from ambient light.