SAR图像ROEWA边缘检测器的改进

刘夯; 何政伟; 赵银兵; 滕靖; 王勇

doi:10.11834/jrs.20176045

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SAR图像ROEWA边缘检测器的改进
Improved ROEWA edge detector for SAR Images
2017年21卷第2期页码：273-279
纸质出版日期： 2017-3 ，

录用日期： 2016-06-10
DOI： 10.11834/jrs.20176045

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刘夯, 何政伟, 赵银兵, 等. SAR图像ROEWA边缘检测器的改进[J]. 遥感学报, 2017,21(2):273-279.

Hang LIU, Zhengwei HE, Yinbing ZHAO, et al. Improved ROEWA edge detector for SAR Images[J]. Journal of Remote sensing, 2017,21(2):273-279.
刘夯, 何政伟, 赵银兵, 等. SAR图像ROEWA边缘检测器的改进[J]. 遥感学报, 2017,21(2):273-279. DOI： 10.11834/jrs.20176045.

Hang LIU, Zhengwei HE, Yinbing ZHAO, et al. Improved ROEWA edge detector for SAR Images[J]. Journal of Remote sensing, 2017,21(2):273-279. DOI： 10.11834/jrs.20176045.

摘要

针对指数加权均值比(ROEWA)边缘检测算子无法准确确定边缘位置和边缘方向的问题，对其表达式进行了改进。重新定义了反转的、带符号的、归一化最小指数加权均值比(IROEWA)，作为边缘强度指标，来量化描述边缘的跃变程度，并在此基础上准确计算出边缘的方位。同时将改进的非极大值抑制算法应用到边缘检测流程中，对IROEWA得到的边缘强度图进行后处理。针对自然SAR图像和仿真SAR图像的实验都表明，改进算法能够得到比ROEWA加分水岭分割的原始算法更好的边缘检测结果。利用接收者操作特征(ROC)曲线，对改进算法进行量化评价，其曲线下面积(AUC)可达0.97570，非常接近理想的检测器；在其ROC曲线的最优点处，检测率可达0.95232，而虚警率仅为0.00214左右。

Abstract

This paper reports on a method to improve the Ratio Of an Exponentially Weighted Averages (ROEWA) edge detector

so that the improved edge detector can accurately determine the positions and directions of edges for Synthetic Aperture Radar (SAR) images. We attempt to build an optimal edge detector for SAR images to obtain better results of edge detection. The edge strength index is redefined as an inverted

signed

and normalized minimum ROEWA (IROEWA)

which is utilized to quantitatively describe the phase step of edges. A new method that accurately calculates edge direction is developed based on the edge strength map from IROEWA. We can obtain the possible values of edge directions in this manner

which continuously distributes from 0 degrees to 180 degrees. Therefore

we must improve the Non-Maximum Suppression (NMS) algorithm

so that it can process sub-pixels. Finally

the improved NMS algorithm is also added into the edge detection workflow. This improved edge detection algorithm is called IROEWA & NMS. We conducted two experiments for IROEWA & NMS: one employed nature SAR images

whereas the other adopted a simulation SAR image. Experiment results show that the IROEWA & NMS outperforms the original ROEWA with watershed thresholding. The IROEWA operator is faster than the ROEWA operator under the same conditions. We applied a Receiver Operating Characteristic (ROC) curve to evaluate the IROEWA & NMS and determined that its Area Under the Curve (AUC) is 0.97570; thus

it approximates the ideal optimal detector. The detection rate at the position of the optimal point in the ROC curve of the IROEWA & NMS is as high as 0.95232

whereas the false alarm rate is as low as 0.00214. The IROEWA & NMS exhibits suitable performance on both the detection and false alarm rates. It has significant application value in several fields

such as the segmentation and edge detection for SAR images.

关键词

合成孔径雷达图像边缘检测指数加权均值比非极大值抑制接收者操作特征曲线

Keywords

SAR imagesedge detectionROEWANon-Maximum Suppression(NMS)Receiver Operating Characteristic(ROC)

references

安成锦, 辛玉林, 陈曾平. 2011. 基于改进ROEWA算子的SAR图像边缘检测方法. 中国图象图形学报, 16(8): 1483–1488

An C J, Xin Y L and Chen Z P. 2011. Edge detection algorithm for SAR image based on improved ROEWA. Journal of Image and Graphics, 16(8): 1483–1488

Bovik A C. 1988. On detecting edges in speckle imagery. IEEE Transactions on Acoustics, Speech, and Signal Processing, 36(10): 1618–1627

Canny J F. 1986. A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-8(6): 679–698

Fjørtoft R, Lopès A, Marthon P and Cubero-Castan E. 1998. An optimal multiedge detector for SAR image segmentation. IEEE Transactions on Geoscience and Remote Sensing, 36(3): 793–802

贾承丽, 匡纲要. 2007. 一种改进的SAR图像边缘检测方法. 电子与信息学报, 29(2): 379–382

Jia C L and Kuang G Y. 2007. An improved edge detection algorithm for SAR images. Journal of Electronics and Information Technology, 29(2): 379–382

Lee J S. 1986. Speckle suppression and analysis for synthetic aperture radar images. Optical Engineering, 25(5): 636–643

Mason S J and Graham N E. 2002. Areas beneath the relative operating characteristics (ROC) and relative operating levels (ROL) curves: statistical significance and interpretation. Quarterly Journal of the Royal Meteorological Society, 128(584): 2145–2166

Paillou P. 1997. Detecting step edges in noisy SAR images: a new linear operator. IEEE Transactions on Geoscience and Remote Sensing, 35(1): 191–196

孙长亮. 2006. 基于ROC曲线的ATR算法性能评估方法研究. 长沙: 国防科学技术大学: 28–31

Sun C L. 2006. Study of ATR Algorithm Performance Evaluation Method based on ROC Curve. Changsha: National University of Defense Technology: 28–31

吴禹昊, 陈天泽, 粟毅. 2010. 基于方向ROEWA算子的高分辨率SAR图像道路提取. 计算机工程与科学, 32(8): 71–74

Wu Y H, Chen T Z and Shu Y. 2010. Road extraction from high resolution SAR images based on the directional ROEWA detector. Computer Engineering and Science, 32(8): 71–74

杨道莲, 鲁昌华, 张金良, 杨凯, 陈晓婷. 2013. 基于ROEWA与Hough变换的SAR图像边缘检测. 电子测量与仪器学报, 27(6): 543–548

Yang D L, Lu C H, Zhang J L, Yang K and Chen X T. 2013. Edge detection in SAR images based on ROEWA and Hough transform. Journal of Electronic Measurement and Instrument, 27(6): 543–548

Zaman M R and Moloney C R. 1993. A comparison of adaptive filters for edge-preserving smoothing of speckle noise // Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing. Minneapolis, MN, USA: IEEE: 77–80 [DOI: 10.1109/ICASSP.1993.319751]

赵凌君, 贾承丽, 匡纲要. 2007. SAR图像边缘检测方法综述. 中国图象图形学报, 12(12): 2042–2049

Zhao L J, Jia C L and Kuang G Y. 2007. Overview of edge detection in SAR images. Journal of Image and Graphics, 12(12): 2042–2049

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