形态学边缘信息引导的区域合并合成孔径雷达图像分割算法

樊书辰; 水鹏朗

doi:10.7652/xjtuxb201910004

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形态学边缘信息引导的区域合并合成孔径雷达图像分割算法

更新时间：2025-07-09

- 形态学边缘信息引导的区域合并合成孔径雷达图像分割算法
- A Segmentation Algorithm for SAR Images Via Region Merging Guided by Morphological Edge Information
- 西安交通大学学报 2019年53卷第10期页码：24-30+47
- 作者机构：
  
  西安电子科技大学雷达信号处理国家重点实验室,西安,710071
- 作者简介：
- 基金信息：
  
  : 2018-11-30。作者简介: 樊书辰(1989—),男,博士生;水鹏朗(通信作者),男,教授,博士生导师。基金项目: 国家自然科学基金资助项目(61671357)
- DOI：10.7652/xjtuxb201910004
  中图分类号： TP751.1
- 网络首发：2019-10-10，
  
  纸质出版：2019
- 稿件说明：
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樊书辰, 水鹏朗. 形态学边缘信息引导的区域合并合成孔径雷达图像分割算法[J]. 西安交通大学学报, 2019,53(10):24-30+47.

A Segmentation Algorithm for SAR Images Via Region Merging Guided by Morphological Edge Information[J]. 2019, 53(10): 24-30+47.
樊书辰, 水鹏朗. 形态学边缘信息引导的区域合并合成孔径雷达图像分割算法[J]. 西安交通大学学报, 2019,53(10):24-30+47. DOI： 10.7652/xjtuxb201910004.

A Segmentation Algorithm for SAR Images Via Region Merging Guided by Morphological Edge Information[J]. 2019, 53(10): 24-30+47. DOI： 10.7652/xjtuxb201910004.

摘要

针对基于区域合并的合成孔径雷达(SAR)图像分割中

初始分割过度碎片化影响后续区域合并效率和质量的问题

提出了利用形态学边缘信息引导的区域合并(MEI-RCBLP)SAR图像分割算法。首先利用高斯和伽马函数赋权的加权中值滤波构造各向异性形态学方向比率算子

提取图像的边缘强度映射来表征边缘响应的强弱

并对边缘强度映射进行阈值化处理和分水岭变换得到高质量的初始分割; 然后利用现有的相对公共边界长度惩罚区域合并技术

迭代地合并初始分割中最相似的相邻区域

直到满足合并终止条件

输出最终的分割结果。实验结果表明

相比利用统计区域生长、MISP超像素和均值比边缘信息引导的分割算法

所提出的MEI-RCBLP算法显著改善了初始分割质量

在保证最终分割质量的前提下初始分割区域数目减少了25%以上

同时最终的分割结果在不同的性能评价指标上总体优于上述对比算法。

Abstract

A segmentation algorithm for SAR images using region merging guided by morphological edge information is proposed to solve the problem that in synthetic aperture radar(SAR)image segmentation based on region merging

the over-fragmentation of initial partition affects the efficiency and quality of subsequent region merging.An anisotropic morphological directional ratio operator is constructed by using the weighted median filtering that is weighted by Gaussian Gamma function to extract the edge strength map(ESM)of an image as the strength of edge responses.Then a thresholding processing and watershed transform are performed on the ESM to obtain a high-quality initial partition.Then

the pair of adjacent regions with the smallest merging cost are iteratively merged using the technique of relative common boundary length penalty

and the final segmentation is outputted until the termination condition of region merging is satisfied.Experimental results and comparisons with methods of the sam

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references

李春升, 王伟杰, 王鹏波, 等.星载SAR技术的现状与发展趋势 [J].电子与信息学报, 2016, 38(1): 229-240.

LI Chunsheng, WANG Weijie, WANG Pengbo, et al.Current situation and development trends of spaceborne SAR technology [J].Journal of Electronics and Information Technology, 38(1): 229-240.

万玲, 尤红建, 程跃兵, 等.合成孔径雷达图像分割研究进展 [J].遥感技术与应用, 2018, 33(1): 10-24.

WAN Ling, YOU Hongjian, CHENG Yuebing, et al.Research progress of synthetic aperture radar image segmentation [J].Remote Sensing Technology and Application, 2018, 33(1): 10-24.

GALLAND F, BERTAUX N, REFREGIER P.Minimum description length synthetic aperture radar image segmentation [J].IEEE Transactions on Image Processing, 2003, 12(9): 995-1006.

MARQUES R C, MEDEIROS F N, SANTOS NOBRE J.SAR image segmentation based on level set approach and G0A model [J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(10): 2046-2057.

ZHANG P, WU Y, LI M, et al.Unsupervised multiclass segmentation of SAR images using fuzzy triplet Markov fields model [J].Pattern Recognition, 2012, 45(11): 4018-4033.

YU P, QIN A K, CLAUSI D A.Unsupervised polarimetric SAR image segmentation and classification using region growing with edge penalty [J].IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(4): 1302-1317.

SHUI P L, ZHANG Z J.Fast SAR image segmentation via merging cost with relative common boundary length penalty [J].IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(10): 6434-6448.

RODRIGUES F A A, NETO J F S R, MARQUES R C P, et al.SAR image segmentation using the roughness information [J].IEEE Geoscience and Remote Sensing Letters, 2016, 13(2): 132-136.

CARVALHO E A, USHIZIMA D M, MEDEIROS F N S, et al.SAR imagery segmentation by statistical region growing and hierarchical merging [J].Digital Signal Processing, 2010, 20(5): 1365-1378.

ARISOY S, KAYABOL K.Mixture-based superpixel segmentation and classification of SAR images [J].IEEE Geoscience and Remote Sensing Letters, 2016, 13(11): 1721-1725.

TOUZI R, LOPES A, BOUSQUET P.Statistical and geometrical edge detector for SAR images [J].IEEE Transactions on Geoscience Remote Sensing, 1988, 26(6): 764-773.

SHUI P L, CHENG D.Edge detector of SAR images using Gaussian-gamma-shaped bi-windows [J].IEEE Geoscience and Remote Sensing Letters, 2012, 9(5): 846-850.

朱磊, 蔡飞飞, 王延年, 等.SAR图像相干斑的非局部平均滤波算法 [J].西安交通大学学报, 2018, 52(4): 98-104.

ZHU Lei, CAI Feifei, WANG Yannian, et al.A non-local means filtering algorithm for despeckling of SAR images [J].Journal of Xi’an Jiaotong University, 2018, 52(4): 98-104.

MARAGOS P, SCHAFER R W.Morphological filters: Part II Their relations to median, order-statistic, and stack filters [J].IEEE Transactions on Acoustics Speech Signal Processing, 1987, 35(8): 1170-1184.

REES W G, SATCHELL M J F.The effect of median filtering on synthetic aperture radar images [J].International Journal of Remote Sensing, 1997, 18(13): 2887-2893.

MA Z, HE K, WEI Y, et al.Constant time weighted median filtering for stereo matching and beyond [C]∥ IEEE International Conference on Computer Vision.Piscataway, NJ, USA: IEEE, 2014: 49-56.

EPPSTEIN D.On nearest-neighbor graphs [J].Discrete Computational Geometry, 1997, 17(3): 263-282.

ARBELAEZ P, MAIRE M, FOWLKES C, et al.Contour detection and hierarchical image segmentation [J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(5): 898-916.

WEI Q R, FENG D Z.An efficient SAR edge detector with a lower false positive rate [J].International Journal of Remote Sensing, 2015, 36(14): 3773-3797.

FERNANDEZ-GARCIA N L, CARMONA-POYATO A, MEDINA-CARNICER R, et al.Automatic generation of consensus ground truth for the comparison of edge detection techniques [J].Image Vision Computing, 2008, 26(4): 496-511.

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