A Real-Time Curve Evolution-Based Image Fusion Algorithm for Multisensory Image Segmentation

© 2003 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper was originally published in the Proceedings of the 2003 IEEE lntemational Conference on Acoustics, Speech, & Signal Processing, April 6-10, 2003, Hong Kong (cancelled). Reprinted with permission.DOI: 10.1109/ICME.2003.1220931A 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