Research on superpixels segmentation of cloud remote sensing images based on density features

Yang Yang; Xinchao Yin; Qi Zhang; Yaxing Sun

doi:10.1117/12.2680422

27 June 2023 Research on superpixels segmentation of cloud remote sensing images based on density features

Yang Yang, Xinchao Yin, Qi Zhang, Yaxing Sun

Proceedings Volume 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022); 127051S (2023) https://doi.org/10.1117/12.2680422
Event: Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 2022, Nanjing, China

Abstract

Remote sensing images are widely used in earth observation. However, the existence of clouds seriously affects the interpretation of remote sensing images. In order to improve the accuracy of cloud detection, it’s usually necessary to complete the segmentation of the cloud boundary before cloud detection. Based on the Simple Linear Iterative Clustering (SLIC) algorithm, an improved SLIC superpixels segmentation method based on density feature is proposed to realize the segmentation of cloud remote sensing images. First, to generate the initial clustering center , the density peak clustering method is used instead of the uniform setting method. Then, in the calculation of distance measurement, we added the local density distance term. Finally, we get the superpixels segmented image by iteration. Four remote sensing images with different underlying surfaces were selected as the test data. The comparison experiments with other two algorithms show that the algorithm promoted in this paper shows superior performance in boundary recall (BR) rate and the error rate is lower than other algorithms in cloud detection.

Citation Download Citation

Yang Yang, Xinchao Yin, Qi Zhang, and Yaxing Sun "Research on superpixels segmentation of cloud remote sensing images based on density features", Proc. SPIE 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 127051S (27 June 2023); https://doi.org/10.1117/12.2680422

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