(Georgia Institute of Technology, 2003-04)
Ding, Yuhua; Vuchtsevunos, George J.; Yezzi, Anthony; Daley, Wayne; Ferri, Bonnie H.
A partial differential equation (PDE)-based feature-level
image fusion approach is proposed for multisensory
image segmentation. The energy functional of the
proposed fusion model is a weighted sum of several
functionals, each constructed based on the characteristics
of the sensor image. The weight selection decides the
way that the model handles redundant, conflicting, or
complementary information involved in the multisensory
data. The method is implemented using level sets and is
fast enough for real-time segmentation tasks. Finally the
algorithm is applied to the segmentation of x-ray and
visual images, and the results show that the fusion
algorithm is efficient, accurate, and robust.
(Georgia Institute of Technology, 2003-04)
Ding, Yuhua; Vuchtsevunos, George J.; Yezzi, Anthony; Daley, Wayne; Ferri, Bonnie H.
A partial differential equation (PDE)-based feature-level image fusion approach is proposed for multisensory image segmentation. The energy functional of the proposed fusion model is a weighted sum of several functionals, each constructed based on the characteristics of the sensor image. The weight selection decides the way that the model handles redundant, conflicting, or complementary information involved in the multisensory data. The method is implemented using level sets and is fast enough for real-time segmentation tasks. Finally the algorithm is applied to the segmentation of x-ray and visual images, and the results show that the fusion algorithm is efficient, accurate, and robust.