[1]王庆,唐涛,项德良,等.基于梯度比率的SAR图像局部特征提取方法研究[J].智能系统学报,2017,12(03):286-292.[doi:10.11992/tis.201603025]
 WANG Qing,TANG Tao,XIANG Deliang,et al.Research on local feature extraction of SAR images based on gradient ratio[J].CAAI Transactions on Intelligent Systems,2017,12(03):286-292.[doi:10.11992/tis.201603025]
点击复制

基于梯度比率的SAR图像局部特征提取方法研究(/HTML)
分享到:

《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第12卷
期数:
2017年03期
页码:
286-292
栏目:
出版日期:
2017-06-25

文章信息/Info

Title:
Research on local feature extraction of SAR images based on gradient ratio
作者:
王庆 唐涛 项德良 粟毅
国防科技大学 电子科学与工程学院, 湖南 长沙 410073
Author(s):
WANG Qing TANG Tao XIANG Deliang SU Yi
School of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China
关键词:
SAR图像特征提取局部二值模式梯度比率旋转不变
Keywords:
SAR imagefeature extractionlocal binary patterngradient ratiorotation-invariant
分类号:
TP751.1
DOI:
10.11992/tis.201603025
摘要:
本文研究了基于像素灰度差值计算的LBP算子和基于梯度比率的LGRP算子等局部二值模式。首先介绍了基本LBP算子和其他几种LBP算子的变形模式,并通过光学图像和实测SAR图像对LBP算子进行性能评估。针对LBP对SAR 图像乘性噪声敏感的问题,利用梯度比率计算的LGRP算子,并结合旋转不变LBP的抗旋转性,本文提出了一种改进的SAR 图像LGRP特征,获得了对SAR 图像的抗噪性和抗旋转性能。实验结果表明,由本文方法提取的SAR图像局部特征具有较好的不变性,可用于姿态角变化下的目标识别与图像纹理切片匹配。
Abstract:
In this study, we investigate a local binary pattern (LBP) operator based on a difference calculation and a local gradient ratio pattern (LGRP) operator based on a gradient ratio. First, we introduce a basic and several other LBP operators and evaluate the performance of the LBP operators using optical image and synthetic aperture radar (SAR) image analysis. To address the problem of LBP’s sensitivity to multiplicative noise in SAR images, we use the LGRP calculator based on the gradient ratio, combined with the anti-rotation characteristics of a rotation-invariant LBP, and propose an improved rotation-invariant LGRP characteristic for SAR images. Our experimental results demonstrate that the proposed feature has good invariant performance in target recognition and image texture slice matching with changes in the angle of attitude.

参考文献/References:

[1] SONG C, YANG F, LI P. Rotation invariant texture measured by local binary pattern for remote sensing image classification[C].Education Technology and Computer Science (ETCS), 2010 Second International Workshop on. IEEE, 2010, 3: 3-6.
[2] OJALA T, M, HARWOOD D. A comparative study of texture measures with classification based on featured distributions[J]. Pattern recognition, 1996, 29(1): 51-59.
[3] AHONEN T, HADID A, M. Face description with local binary patterns: Application to face recognition[J]. IEEE transactions on pattern analysis and machine intelligence, 2006, 28(12): 2037-2041.
[4] AHONEN T, HADID A, M. Face recognition with local binary patterns[J].European conference on computer vision, 2004,3021 (12) : 469-481.
[5] NING J, ZHANG L, ZHANG D, et al. Robust object tracking using joint color-texture histogram[J]. International journal of pattern recognition and artificial intelligence, 2009, 23(07): 1245-1263.
[6] Topi M, Timo O, Matti P, et al. Robust texture classification by subsets of local binary patterns[C]//Proceedings of the 15th International Conference on Pattern Recognition. 2000. IEEE, 2000, 3(3): 935-938.
[7] Ojala T, Pietikäinen M, Mäenpää T. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns[J]. IEEE transactions on pattern analysis and machine intelligence,2002, 24(7): 971-987.
[8] DAI D, YANG W, SUN H. Multilevel local pattern histogram for SAR image classification[J]. IEEE geoscience and remote sensing letters, 2011, 8(2): 225-229.
[9] 项德良,粟毅,赵凌君,等. 一种基于局部梯度比率特征度量SAR图像相似性的新方法[J]. 电子学报,2014,01:9-13.XIANG Deliang, SU Yi, ZHAO Lingjun, et al. A new algorithm for SAR imagery similarity measure based on local gradient ratio pattern[J].Acta electronica sinica,2014,01: 9-13.
[10] GUAN Dongdong, TANG Tao, ZHAO Ling-jun, et al. A feature combining spatial and structural information for SAR image classification[C].Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International. IEEE, 2015: 4396-4399.
[11] LI L, TONG C S, CHOY S K. Texture classification using refined histogram[J]. IEEE transactions on image processing, 2010, 19(5):

相似文献/References:

[1]黄剑华,唐降龙,刘家锋,等.一种基于Homogeneity的文本检测新方法[J].智能系统学报,2007,2(01):69.
 HUANG Jian-hua,TANG Xiang-long,LIU Jia-feng,et al.A new method for text detection based on Homogeneity[J].CAAI Transactions on Intelligent Systems,2007,2(03):69.
[2]谭 营,朱元春.反垃圾电子邮件方法研究进展[J].智能系统学报,2010,5(03):189.
 TAN Ying,ZHU Yuan-chun.Advances in antispam techniques[J].CAAI Transactions on Intelligent Systems,2010,5(03):189.
[3]王斐,张育中,宁廷会,等.脑-机接口研究进展[J].智能系统学报,2011,6(03):189.
 WANG Fei,ZHANG Yuzhong,NING Tinghui,et al.Research progress in a braincomputer interface[J].CAAI Transactions on Intelligent Systems,2011,6(03):189.
[4]刘琚,孙建德.独立分量分析的图像/视频分析与应用[J].智能系统学报,2011,6(06):495.
 LIU Ju,SUN Jiande.Independent component analysisbased image/video analysis and applications[J].CAAI Transactions on Intelligent Systems,2011,6(03):495.
[5]谭营,王军.手指静脉身份识别技术最新进展[J].智能系统学报,2011,6(06):471.
 TAN Ying,WANG Jun.Recent advances in finger vein based biometric techniques[J].CAAI Transactions on Intelligent Systems,2011,6(03):471.
[6]吴家伟,严京旗,方志宏,等.基于图像显著性特征的铸坯表面缺陷检测[J].智能系统学报,2012,7(01):75.
 WU Jiawei,YAN Jingqi,FANG Zhihong,et al.Defect detection on a steel slab surface based on the characteristics of an image’s saliency region[J].CAAI Transactions on Intelligent Systems,2012,7(03):75.
[7]张毅,罗明伟,罗元.脑电信号的小波变换和样本熵特征提取方法[J].智能系统学报,2012,7(04):339.
 ZHANG Yi,LUO Mingwei,LUO Yuan.EEG feature extraction method based on wavelet transform and sample entropy[J].CAAI Transactions on Intelligent Systems,2012,7(03):339.
[8]刘忠宝,王士同.从Parzen窗核密度估计到特征提取方法:新的研究视角[J].智能系统学报,2012,7(06):471.
 LIU Zhongbao,WANG Shitong.From Parzen window estimation to feature extraction: a new perspective[J].CAAI Transactions on Intelligent Systems,2012,7(03):471.
[9]孙倩茹,王文敏,刘宏.视频序列的人体运动描述方法综述[J].智能系统学报,2013,8(03):189.
 SUN Qianru,WANG Wenmin,LIU Hong.Study of human action representation in video sequences[J].CAAI Transactions on Intelligent Systems,2013,8(03):189.
[10]许可乐,唐涛,蒋咏梅.一种SAR图像稳健特征点提取方法[J].智能系统学报,2013,8(04):287.[doi:10.3969/j.issn.1673-4785.201304038]
 XU Kele,TANG Tao,JIANG Yongmei.A stable feature point extraction approach for SAR image registration[J].CAAI Transactions on Intelligent Systems,2013,8(03):287.[doi:10.3969/j.issn.1673-4785.201304038]

备注/Memo

备注/Memo:
收稿日期:2016-03-16。
基金项目:国家自然科学基金(61401477).
作者简介:王庆,女,1990年,硕士研究生,主要研究方向为新体制雷达;唐涛,男,1980年,讲师,主要研究方向为遥感图像解译、SAR图像目标特征提取;项德良,男,1989年,博士研究生,主要研究方向为SAR图像处理。
通讯作者:王庆.E-mail:290720609@qq.com.
更新日期/Last Update: 2017-06-25