Analysis of the optical flow model applied to the motion estimation of sea ice from ERS-1 SAR image sequences

Aisheng Li; Jan Askne

doi:10.1117/12.262686

17 December 1996 Analysis of the optical flow model applied to the motion estimation of sea ice from ERS-1 SAR image sequences

Aisheng Li, Jan Askne

Author Affiliations +

Proceedings Volume 2958, Microwave Sensing and Synthetic Aperture Radar; (1996) https://doi.org/10.1117/12.262686
Event: Satellite Remote Sensing III, 1996, Taormina, Italy

Abstract

The optical flow models have been widely used in computer vision and recently also applied to motion estimation of sea ice with SAR satellite image sequences. However, the optical flow models, which are commonly based on the assumptions that the image brightness is stationary and velocity field or optical flow is constant within a small neighborhood, are sensitive to conditions usually encountered in real imagery. It is of interest and important to analyze the error sources and adaptability of optical flow models to real imagery. From similar assumptions, different optical flow methods can be derived. In particular, the optical flow model based on the second order partial derivatives of image brightness is emphasized because of its immunity to the aperture problem. The attention in the paper is paid to the analysis of this optical flow model. Based on error analysis, this paper discusses the adaptability of the optical flow model and the estimated accuracy of the velocity field in motion estimation of sea ice from ERS-1 SAR image sequences. Some experimental results of motion estimation from ERS-1 SAR images of sea ice in the Arctic area are presented in the paper, and some conclusions are finally drawn.

Citation Download Citation

Aisheng Li and Jan Askne "Analysis of the optical flow model applied to the motion estimation of sea ice from ERS-1 SAR image sequences", Proc. SPIE 2958, Microwave Sensing and Synthetic Aperture Radar, (17 December 1996); https://doi.org/10.1117/12.262686

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