I am a cs student who's doing a project in satellite images.
My project is:
Input: satellite images from MSG European satellite. Those are colored
images which come along with text files that physically represent every
pixel in the image (i mean that every pixel has a record in the text
file which says what is the IR, temp' reflectance & more in that
specific pixel)
- deriving the clouds from the complete image & building in c++ a very
large 2D matrix which represent the image in binary: 1 for cloud
existence & 0 otherwise.
- correlating between two sequential images & deriving the clouds
direction vector. That way i can speculate the clouds general motion
(direction).

My questions for you:
1.Can you suggest a better way to preform this actions?
2. I need to correlate between 2 binary matrices via 'cross
correlation' method & i really don't know how to implement it in c++
since it's very complexed (honestly, i prefer finding a source file &
invest my time surfing)
3. Based on your experience in this field: Does cross correlation is
the best way to compute direction vector for those matrices (which
reform every second..)? what about other block matching methods?
Can you write down something that helps?

I appreciate any help!
Peace & sun shine forever,