Cross Correlation Matrix In my group, we have developed an algorithm which shows abstract information from quantum mechanical systems as images. This way, given a quantum system, we obtain an associated image which has the same information and makes some features visible.

One of the important features is obtained using a "cross-correlation matrix": We divide the image into $L\times L$ sub-images and find the "overlap" between all pairs. So, the entry for sub-images $i$ and $j$, $A_{i,j}$ is a number stating how similar they are. The matrix dimension is $L^2\times L^2$.

The question is: is this matrix, or a close relative, used in image-processing? If it does, does it have a name? Does it have any interesting properties, or does it help for any useful algorithms?
If you look around for "image patch self-similarity" there are some things that are along those lines, for example the work of Eli Shechtman and Michal Irani

http://www.wisdom.weizmann.ac.il/~vision/SelfSimilarities.html

or the Calvin research centre:

http://www.vision.ee.ethz.ch/~calvin/software.html

(see Global and Efficient Self-Similarity for Object Classification and Detection)