Gravitation-based edge detection in hyperspectral images

Sun, Genyun; Zhang, Aizhu; Ren, Jinchang; Ma, Jingsheng; Wang, Peng; Zhang, Yuanzhi; Jia, Xiuping

Abstract

Edge detection is one of the key issues in the field of computer vision and remote sensing image analysis. Although many different edge-detection methods have been proposed for gray-scale, color, and multispectral images, they still face difficulties when extracting edge features from hyperspectral images (HSIs) that contain a large number of bands with very narrow gap in the spectral domain. Inspired by the clustering characteristic of the gravitational theory, a novel edge-detection algorithm for HSIs is presented in this paper. In the proposed method, we first construct a joint feature space by combining the spatial and spectral features. Each pixel of HSI is assumed to be a celestial object in the joint feature space, which exerts gravitational force to each of its neighboring pixel. Accordingly, each object travels in the joint feature space until it reaches a stable equilibrium. At the equilibrium, the image is smoothed and the edges are enhanced, where the edge pixels can be easily distinguished by calculating the gravitational potential energy. The proposed edge-detection method is tested on several benchmark HSIs and the obtained results were compared with those of four state-of-the-art approaches. The experimental results confirm the efficacy of the proposed method.

Citation

SUN, G., ZHANG, A., REN, J., MA, J., WANG, P., ZHANG, Y. and JIA, X. 2017. Gravitation-based edge detection in hyperspectral images. Remote sensing [online], 9(6), article 592. Available from: https://doi.org/10.3390/rs9060592

• Journal Article Type: Article
• Acceptance Date: Jun 8, 2017
• Online Publication Date: Jun 11, 2017
• Publication Date: Jun 30, 2017
• Deposit Date: Jul 1, 2022
• Publicly Available Date: Jul 1, 2022
• Journal: Remote Sensing
• Electronic ISSN: 2072-4292
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 9
• Issue: 6
• Article Number: 592
• DOI: https://doi.org/10.3390/rs9060592
• Keywords: Edge detection; Hyperspectral image; Gravitation; Remote sensing; Feature space
• Public URL: https://rgu-repository.worktribe.com/output/1085415
• Additional Information: An earlier preprint version of this article was made available at https://www.preprints.org/manuscript/201705.0142/v1