Authors: Deqiang Han, Jean Dezert, Shicheng Li, Chongzhao Han, Yi Yang
Image registration is a crucial and necessary step before image fusion. It aims to achieve the optimal match between two or more images of the same scene taken at different times, from different viewpoints, and/or by different sensors. In the procedure of image registration, several types of uncertainty will be encountered, e.g., the selection of control points and the distance or the dissimilarity measures used for image matching. In this paper, we model these uncertainty in image registration using the theory of belief functions. By jointly using the pixel level and feature level information, more effective image registrations are accomplished. Experimental results, comparisons and related analyses illustrate the effectiveness of our evidential reasoning based image registration approach.
Comments: 8 Pages.
Download: PDF
[v1] 2014-12-04 03:18:45
Unique-IP document downloads: 119 times
Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.
Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.