Detection of Outer Rotations on 3D-Vector Fields with Iterative Geometric Correlation and its Efficiency
This addresses a specific challenge in color image processing for researchers and practitioners, offering an incremental improvement over prior limited methods.
The paper tackles the problem of detecting arbitrary 3D outer rotational misalignments in vector fields, proving that iterative geometric correlation can achieve this and presenting an algorithm with experimental acceleration that shows great success.
Correlation is a common technique for the detection of shifts. Its generalization to the multidimensional geometric correlation in Clifford algebras has been proven a useful tool for color image processing, because it additionally contains information about a rotational misalignment. But so far the exact correction of a three-dimensional outer rotation could only be achieved in certain special cases. In this paper we prove that applying the geometric correlation iteratively has the potential to detect the outer rotational misalignment for arbitrary three-dimensional vector fields. We further present the explicit iterative algorithm, analyze its efficiency detecting the rotational misalignment in the color space of a color image. The experiments suggest a method for the acceleration of the algorithm, which is practically tested with great success.