Batch Normalized Cross-Correlation
By TC
Description
The purpose of the batch NCC is to be able to see what areas of the topography are strongest and weakest. In general, this will be performed on the the high resolution maplets that make up the topography in question, but this process will work for any given list of maplets. Following this guide will run norm_xcorr.py for each maplet specified in your input list, as well as provide several useful statistics and plots for analysis.
Setup
There are a few prerequisites to get in order before processing can begin. First of which is gathering files. Links to text versions of all of the script files I use are provided, but feel free to adapt them to your needs, or write new ones!
Step 1: Create a directory called COROUT in your working directory. (Can be called whatever you'd like but this will require updating the scripts)
mkdir COROUT
Step 2: Place the search image inside of COROUT. For our purposes this is generally an image rendered from the truth model using Showmap
cp /whatever/path/truth.pgm COROUT/
Step 3: Add the truth .MAP file to your MAPFILES directory, and update BIGLIST.TXT. Generally speaking it is bad form to have a truth map in your MAPFILES directory, but as long as this is for post-processing analysis it should be fine. It may be best to create a symbolic link.
ln -s /path/to/TRUTH.MAP MAPFILES/TRUTH.MAP vi BIGLIST.TXT (insert truth map name in BIGLIST.TXT)