A prior shape-based level-set method for auroral oval segmentation. Issue 3 (4th March 2019)

• Record Type: Journal Article
• Authors: Meng, Yong; Zhou, Zeming; Liu, Yudi; Luo, Qixiang; Yang, Pinglv; Li, Miaoying
• Is Part Of: Remote sensing letters. Volume 10:Issue 3(2019)
• Page Start: 292
• Page End: 301
• Publication Date: 2019-03-04
• Subjects: Remote sensing -- Periodicals; Remote sensing; Periodicals; 621.3678
• DOI: 10.1080/2150704X.2018.1547928
• Languages: English
• ISSNs: 2150-704X

Abstract

ABSTRACT: Low-contrast and dayglow contamination pose a challenge to the accurate contour extraction of the auroral oval captured by the ultraviolet imager (UVI). To address the segmentation difficulties, a novel prior shape-based level-set method (PSLSM) is proposed by introducing prior knowledge into the variational framework. Firstly, driven by the local information term and the distance constraint term, a preliminary contour containing inner and outer boundary of the aurora is acquired. After that, the contour is employed to reconstruct a prior shape to guide the zero-level-set curve evolving to the actual position of the auroral oval, based on the shape dictionary which is formed with the aligned training samples. Compared with the recently proposed state-of-the-art methods, the contour tracking experiments demonstrate that PSLSM can provide a more competitive segmentation result.