基于块近邻的边界约束标签平滑高光谱图像分类方案

doi:10.3969/j.issn.1000-3428.2017.11.040

计算机工程

基于块近邻的边界约束标签平滑高光谱图像分类方案

陈善学,桂成名,王一宁

(重庆邮电大学移动通信技术重庆市重点实验室,重庆 400065)

收稿日期:2016-10-25 出版日期:2017-11-15 发布日期:2017-11-15
作者简介:陈善学(1966—),男,教授、博士,主研方向为图像处理、数据压缩;桂成名、王一宁,硕士研究生。
基金资助:
重庆市教委科学技术研究项目(KJ1400416)。

Hyperspectral Image Classification Scheme with Boundary Constrain Label Smoothing Based on Block Neighbor

CHEN Shanxue,GUI Chengming,WANG Yining

(Chongqing Key Lab of Mobile Communications Technology,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)

Received:2016-10-25 Online:2017-11-15 Published:2017-11-15

摘要/Abstract

摘要： 为提高高光谱图像分类精度,结合光谱信息、邻域信息和边界信息提出一种高光谱图像分类方案。利用局部费希尔判别分析算法进行降维操作并获取边界信息。根据块近邻分类器算法结合光谱和邻域2个维度获得判决信息。采用边界信息对块近邻分类器算法获得的分类标签进行标签平滑操作。在3个真实地物高光谱数据集上进行实验,结果表明该方案稳定有效地提高了高光谱图像的分类精度。

关键词: 高光谱图像分类, 块近邻分类器, 标签平滑, 边界约束, 局部费希尔判别分析

Abstract: In order to improve the accuracy of hyperspectral image classification,combined with spectral information,neighborhood information and boundary information,this paper proposes a hyperspectral image classification scheme.The method takes the Local Fisher Discriminant Analysis(LFDA) algorithm to reduce the dimension and get the boundary information.The proposed Block Nearest Classifier(BNC) algorithm is used to get the discriminant information with the spectral feature and neighbor feature.The boundary information is used to smooth the classification label obtained from BNC algorithm.Experiment is carried out on hyperspectral dataset of 3 real ground objects.Results show that the proposed scheme improves the classification accuracy of hyperspectral imag effectively and robust.

Key words: hyperspectral image classification, Block Neighbor Classifier(BNC), label smoothing, boundary constrain, local Fisher discriminant analysis

中图分类号:

TP301.6

陈善学,桂成名,王一宁. 基于块近邻的边界约束标签平滑高光谱图像分类方案[J]. 计算机工程, doi: 10.3969/j.issn.1000-3428.2017.11.040.

CHEN Shanxue,GUI Chengming,WANG Yining. Hyperspectral Image Classification Scheme with Boundary Constrain Label Smoothing Based on Block Neighbor[J]. Computer Engineering, doi: 10.3969/j.issn.1000-3428.2017.11.040.

http://www.ecice06.com/CN/Y2017/V43/I11/245

参考文献

参考文献［1］HUANG Kunshan,LI S,KANG Xudong,et al.Spectral-Spatial Hyperspectral Image Classification Based on KNN［J］.Sensing & Imaging,2016,17(1):1-13. ［2］刘建军,吴泽彬,韦志辉,等.基于空间相关性约束稀疏表示的高光谱图像分类［J］.电子与信息学报,2012,34(11):2666-2671. ［3］QIAN Yuntao,YE Minchao,ZHOU Jun.Hyperspectral Image Classification Based on Structured Sparse Logistic Regression and Three-Dimensional Wavelet Texture Features［J］.IEEE Transactions on Geoscience & Remote Sensing,2013,51(4):2276-2291. ［4］GOTSIS P K,CHAMIS C C,MINNETYAN L.Classification of Hyperspectral Remote Sensing Images with Support Vector Machines［J］.IEEE Transactions on Geoscience & Remote Sensing,2004,19(3):753-773. ［5］ZHANG Zhou,Pasolli E,Crawford M M,et al.An Active Learning Framework for Hyperspectral Image Classification Using Hierarchical Segmentation［J］.IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing,2016,9(2):640-654. ［6］LI Wei,PRASAD S,FOWLER J E.Hyperspectral Image Classification Using Gaussian Mixture Models and Markov Random Fields［J］.IEEE Geoscience & Remote Sensing Letters,2014,11(1):153-157. ［7］宋相法,焦李成.基于稀疏表示及光谱信息的高光谱遥感图像分类［J］.电子与信息学报,2012,34(2):268-272. ［8］唐晓晴,刘亚洲,陈骏龙.基于稀疏表示的遥感图像分类方法改进［J］.计算机工程,2016,42(3):254-258,265. ［9］CHEN Xu,RAMADGE P J.Collaborative Repre-sentation,Sparsity or Nonlinearity:What is Key to Dictionary Based Classification?［C］//Proceedings of IEEE International Conference on Acoustics,Speech and Signal Processing.Washington D.C.,USA:IEEE Press,2014:5227-5231. ［10］CALVO-ZARAGOZA J,VALERO-MAS J J,RICO-JUAN J R.Improving kNN Multi-label Classification in Prototype Selection Scenarios Using Class Proposals［J］.Pattern Recognition,2015,48(5):1608-1622. ［11］BENEDIKTSSON J A,PESARESI M,AMASON K.Classification and Feature Extraction for Remote Sensing Images from Urban Areas Based on Morphological Transformations［J］.IEEE Transactions on Geoscience & Remote Sensing,2003,41(9):1940-1949. ［12］GU Yanfeng,LIU Tianzhu,JIA Xiuping,et al.Nonlinear Multiple Kernel Learning with Multiple-Structure-Element Extended Morphological Profiles for Hyperspectral Image Classification［J］.IEEE Transactions on Geoscience & Remote Sensing,2016,54(6):1-13. ［13］KANG Xudong,LI Shutao,BENEDIKTSSON J A.Spectral-spatial Hyperspectral Image Classification with Edge-preserving Filtering［J］.IEEE Transactions on Geoscience & Remote Sensing,2014,52(5):2666-2677. ［14］ZHANG Lefei,ZHANG Qian,ZHANG Liangpei,et al.Ensemble Manifold Regularized Sparse Low-rank Approximation for Multiview Feature Embedding［J］.Pattern Recognition,2015,48(10):3102-3112. ［15］VAN Mien,KANG Hee-jun.Wavelet Kernel Local Fisher Discriminant Analysis with Particle Swarm Optimization Algorithm for Bearing Defect Classification［J］.IEEE Transactions on Instrumentation & Measurement,2015,64(12):3588-3600. ［16］ZHAI Yongguang,ZHANG Lifu,WANG Nan,et al.A Modified Locality-preserving Projection Approach for Hyperspectral Image Classification［J］.IEEE Geoscience & Remote Sensing Letters,2016,13(8):1059-1063. ［17］WU Hao,PRASAD S,CUI Minshan,et al.Hyperspectral Image Classification Based on Dirichlet Process Mixture Models［C］//Proceedings of IEEE International Geoscience and Remote Sensing Symposium.Washington D.C.,USA:IEEE Press,2013:1043-1046. ［18］ZHANG Hongyan,LI Jiayi,HUANG Yuancheng,et al.A Nonlocal Weighted Joint Sparse Representation Classification Method for Hyperspectral Imagery［J］.IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing,2014,7(6):2056-2065. 编辑顾逸斐

[1]	丰芳宇, 罗晓曙, 蒙志明, 王广宇. 基于抗混叠残差注意力网络的人脸表情识别[J]. 计算机工程, 2023, 49(8): 190-198.
[2]	张家钧, 唐云祁, 杨智雄. 融合自适应感受野与多支路特征的鞋型识别算法[J]. 计算机工程, 2022, 48(6): 295-303.
[3]	黄利国, 韩丛英, 孙莉. 基于变量转换的并行优化算法[J]. 计算机工程, 2010, 36(23): 34-35.
[4]	邓长寿;梁昌勇. 解0-1背包问题的混合编码贪婪DE算法[J]. 计算机工程, 2009, 35(23): 24-26.

选择文件类型/文献管理软件名称

选择包含的内容

基于块近邻的边界约束标签平滑高光谱图像分类方案

Hyperspectral Image Classification Scheme with Boundary Constrain Label Smoothing Based on Block Neighbor

PDF

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 4

编辑推荐

Metrics

本文评价

模态框（Modal）标题

选择文件类型/文献管理软件名称

选择包含的内容

基于块近邻的边界约束标签平滑高光谱图像分类方案

Hyperspectral Image Classification Scheme with Boundary Constrain Label Smoothing Based on Block Neighbor

PDF

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 4

编辑推荐

Metrics

本文评价