基于MSERS与SURF算法融合的无人机近红外光谱非稳态影像配准
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摘要
本文面向灾害应急的无人机遥感影像快速拼接融合算法的研究,满足灾害应急对灾情影像数据时效性的需求。为研究算法的融合改进对无人机近红外遥感影像精度的提升问题,利用SURF计算效率高和MSERS能够提取完全仿射不变区域特征的特点,提出了无人机遥感影像特征提取与匹配的方法,该方法是基于SURF融合特征,在影像和尺度空间均具有稳定性且具有多尺度仿射不变的可靠性。并对MS-MSERS、MSERS+SIFT、MSERS+SURF三种算法进行配准效果验证。结果表明:MSERS+SURF的匹配正确率优于其他两种算法。该算法实现了MSERS的多尺度检测及拼接效率成果较好的平衡。
This article discusses the application of fast fusion algorithm to UAV remote sensing images; thus, fulfilling the needs of disaster emergency response. In order to enhance UAV remote sensing images and improve accuracy of near infrared imaging by fusion algorithm—making use of the characteristics of SURF(high calculation efficiency) and MSERS(ability to fully extract the affine invariant region features)—a method for extraction of remote sensing human images and matching, which is reliable and efficient in image and scale space, is put forward. And the effect of registration and verification of MS-MSERS, MSERS+SIFT, MSERS+SURF—three kinds of algorithms is ascertained. The results show that the matching accuracy of MSERS+SURF is better than the other two algorithms. The algorithm achieves multi-scale detection of MSERS and a good balance between stitching efficiency and stitching results.
This article discusses the application of fast fusion algorithm to UAV remote sensing images; thus, fulfilling the needs of disaster emergency response. In order to enhance UAV remote sensing images and improve accuracy of near infrared imaging by fusion algorithm—making use of the characteristics of SURF(high calculation efficiency) and MSERS(ability to fully extract the affine invariant region features)—a method for extraction of remote sensing human images and matching, which is reliable and efficient in image and scale space, is put forward. And the effect of registration and verification of MS-MSERS, MSERS+SIFT, MSERS+SURF—three kinds of algorithms is ascertained. The results show that the matching accuracy of MSERS+SURF is better than the other two algorithms. The algorithm achieves multi-scale detection of MSERS and a good balance between stitching efficiency and stitching results.
引文
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[3]Clark J.Remote sensing and geospatial support to BAER teems in assessing wildfire effects to Hillslopes[M]//Landslide Science and Practical,Berlin,Heidelberg:Springer,2013:211-223.
[4]曾涛,杨武年,简季.无人机低空遥感影像处理在汶川地震地质灾害信息快速勘测中的应用[J].测绘科学,2009(S2):64-65,55.ZENG Tao,YANG Wunian,JIAN Ji.Applications of remote sensing images processing of unmanned air vehicle on the low Attitude in quick acquirement of geological disasters information in Wenchuan earthquake[J].Science of Surveying and Mapping,2009(S2):64-65,55.
[5]尹鹏飞,尹球,陈兴峰,等.无人机航空遥感技术在震后灾情调查中的应用[J].激光与光电子学进展,2010(11):130-134.YIN Pengfei,YIN Qiu,CHEN Xingfeng,et al.Unmanned aerial vehicle aerial remote sensing techniques and its application on post-earthquake disaster investigation[J].Laser&Optoelectronics Progress,2010(11):130-134.
[6]徐海祥,曹万华,陈炜,等.无人机红外舰船目标分割[J].计算机工程与应用,2009,45(8):224-248.XU Haixiang,CAO Wanhua,CHEN Wei,et al.Segmentation of unmanned aerial vehicle infrared ship target[J].Computer Engineering and Applications,2009,45(8):224-248.
[7]Heintz F,Rudol P,Doherty P.From images to traffic behavior-a UAV tracking and monitoring application[C]//10th Conference of the International Society of Information Fusion,2007:1-8.
[8]Rodriguez Pedro A,Geckle William J,Barton Jeffrey D,et al.An emergency response UAV surveillance System[C]//AMIA Symposium,2006:1078.
[9]朱伟,孙久运,刘凯凯.基于最小二乘影像匹配的超分辨率重建[J].地理与地理信息科学,2014(2):116-119.ZHU Wei,SUN Jiuyun,LIU Kaikai.Super-resolution reconstruction based in least squares in age matching[J].Geography and GeoInformation Science,2014(2):116-119.