Log-Euclidean distance based superpixel segmentation for PolSAR images
- DOI
- 10.2991/icmia-16.2016.71How to use a DOI?
- Keywords
- SLIC, polarimetric synthetic aperture radar, Log-Euclidean distance, Postprocessing
- Abstract
The simple linear iterative clustering (SLIC) method is a popular recently proposed superpixel algorithm for its simpleness and good performance for optical images. However, it may provide poor superpixels for polarimetric synthetic aperture radar (PolSAR) images because of the inherent speckle noise. In this paper, an improved SLIC based on Log-Euclidean distance with a novel postprocessing procedure by iteratively merging similar superpixels as well as preserving strong point targets is proposed. Experiments on a real image from ESAR demonstrate its superiority over two state-of-the-art algorithms, i.e., SLIC-GC and standard SLIC.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Hongyan Kang AU - Yue Zhang AU - Huanxin Zou AU - Tiancheng Luo PY - 2016/11 DA - 2016/11 TI - Log-Euclidean distance based superpixel segmentation for PolSAR images BT - Proceedings of the 2016 5th International Conference on Measurement, Instrumentation and Automation (ICMIA 2016) PB - Atlantis Press SP - 397 EP - 400 SN - 1951-6851 UR - https://doi.org/10.2991/icmia-16.2016.71 DO - 10.2991/icmia-16.2016.71 ID - Kang2016/11 ER -