A robust active contour edge detection algorithm based on local Gaussian statistical model for oil slick remote sensing image

Yu Jing; Yaxuan Wang; Jianxin Liu; Zhaoxia Liu

doi:10.1117/12.2197120

10 August 2015 A robust active contour edge detection algorithm based on local Gaussian statistical model for oil slick remote sensing image

Yu Jing, Yaxuan Wang, Jianxin Liu, Zhaoxia Liu

Author Affiliations +

Proceedings Volume 9620, 2015 International Conference on Optical Instruments and Technology: Optical Sensors and Applications; 962019 (2015) https://doi.org/10.1117/12.2197120
Event: International Conference on Optical Instruments and Technology 2015, 2015, Beijing, China

Abstract

Edge detection is a crucial method for the location and quantity estimation of oil slick when oil spills on the sea. In this paper, we present a robust active contour edge detection algorithm for oil spill remote sensing images. In the proposed algorithm, we define a local Gaussian data fitting energy term with spatially varying means and variances, and this data fitting energy term is introduced into a global minimization active contour (GMAC) framework. The energy function minimization is achieved fast by a dual formulation of the weighted total variation norm. The proposed algorithm avoids the existence of local minima, does not require the definition of initial contour, and is robust to weak boundaries, high noise and severe intensity inhomogeneity exiting in oil slick remote sensing images. Furthermore, the edge detection of oil slick and the correction of intensity inhomogeneity are simultaneously achieved via the proposed algorithm. The experiment results have shown that a superior performance of proposed algorithm over state-of-the-art edge detection algorithms. In addition, the proposed algorithm can also deal with the special images with the object and background of the same intensity means but different variances.

Citation Download Citation

Yu Jing, Yaxuan Wang, Jianxin Liu, and Zhaoxia Liu "A robust active contour edge detection algorithm based on local Gaussian statistical model for oil slick remote sensing image", Proc. SPIE 9620, 2015 International Conference on Optical Instruments and Technology: Optical Sensors and Applications, 962019 (10 August 2015); https://doi.org/10.1117/12.2197120

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