Globally consistent image mosaicing

Zezhong Xu; Yanbin Zhuang

doi:10.1117/12.866954

20 August 2010 Globally consistent image mosaicing

Zezhong Xu, Yanbin Zhuang

Proceedings Volume 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering; 78202C (2010) https://doi.org/10.1117/12.866954
Event: International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 2010, Xi'an, China

Abstract

Image mosaicing is widely used in computer vision applications. Accurate and consistent alignment of sequence images is the key issue to image mosaicing. In this paper, a globally consistent image mosaicing is proposed by taking account of various uncertainties. The problem of global alignment of a sequence of images is considered as a stochastic estimation problem. The transformation parameters of images are considered as system state. System augmentation model and system observation model are constructed. The global homographies parameters of sequence images are estimated recursively with augmented Kalman filter in a common state vector and covariance matrix. The proposed image alignment method can handle the uncertainty efficiently and is globally consistent. Some experimental results are provided to validate the performance of the proposed method.

Citation Download Citation

Zezhong Xu and Yanbin Zhuang "Globally consistent image mosaicing", Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 78202C (20 August 2010); https://doi.org/10.1117/12.866954

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available