PROJECT TITLE :
Why Does Mutual-Information Work for Image Registration? A Deterministic Explanation
This paper proposes a deterministic rationalization for mutual-information-primarily based image registration (MI registration). The explanation is that MI registration works because it aligns sure image partitions. This notion of aligning partitions is new, and is shown to be connected to Schur- and quasi-convexity. The partition-alignment theory of this paper goes beyond explaining mutual- data. It suggests other objective functions for registering images. Some of these newer objective functions are not entropy-based. Simulations with noisy images show that the newer objective functions work well for registration, lending support to the theory. The idea proposed in this paper opens a variety of directions for any research in image registration. These directions also are mentioned.
Did you like this research project?
To get this research project Guidelines, Training and Code... Click Here