Cart (Loading....) | Create Account
Close category search window
 

A Kalman filter-based approach for adaptive restoration of in-vehicle camera foggy images

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Hiramatsu, T. ; Grad. Sch. of Inf. Sci. & Technol., Hokkaido Univ., Sapporo ; Ogawa, T. ; Haseyama, M.

In this paper, a Kalman filter-based approach for adaptive restoration of video images acquired by an in-vehicle camera in foggy conditions is proposed. In order to realize Kalman filter-based restoration, the proposed method regards the intensities in each frame as elements of the state variable of the Kalman filter and designs the following two models for restoration of foggy images. The first one is an observation model, which represents a fog deterioration model. The second one is a non-linear state transition model, which represents the target frame in the original video image from its previous frame based on motion vectors. By utilizing the observation and state transition models, the correlation between successive frames can be effectively utilized for restoration. Further, the proposed method introduces a new estimation scheme of the parameter, which determines the deterioration characteristic in foggy conditions, into the Kalman filter algorithm. Consequently, since automatic determination of the fog deterioration model, which specifies the observation model, from only the foggy images is realized, the accurate restoration can be achieved. Experimental results show that the proposed method has better performance than that of the traditional method based on the fog deterioration model.

Published in:

Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on

Date of Conference:

12-15 Oct. 2008

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.