Abstract:
Image registration is the process of matching different images whether 2D or 3D of certain similar or common properties for different purposes. This work addresses this field using a Gauss-Newton optimization approach. The problem is basically formulated as minimizing a cost function that is then solved by a backtracking line search. Since this is considered as a demanding problem especially for larger data, this paper presents the solution using the CUDA GPU architecture provided by Nvidia [1] in order to achieve better performance and reduce timing through parallelism.

Paper available at IEEE.