浏览全部资源
扫码关注微信
Received：12 August 2019，
Published：07 February 2021
移动端阅览
几何配准是影像后续处理的重要前提，是遥感信息处理领域研究的热点之一。复杂地形区多时相遥感影像的高精度配准一直是难以突破的难题，光流估计法通过逐像素位移增量解算为此提供了可行的解决思路，但光流法对地物变化异常敏感，经常导致计算的光流场及配准影像存在异常。为此，本文提出一种基于光流校正的复杂地形区多时相遥感影像配准方法，采用亮度和梯度双重约束获取光流场初值，在此基础上使用高斯拉普拉斯算子对异常光流进行检测，然后通过Delaunay三角形曲面插值对异常光流进行校正处理，从而得到各像素精准位移。实验表明，本文提出方法对存在地物变化的复杂地形区多时相遥感影像，可实现高保真、高精度的配准。
Image registration is a process of geometric alignment of two or more images acquired at different time
different sensors or under different conditions (weather
illumination
camera position and angle
etc.). Remote sensing image registration is an important prerequisite for subsequent processing
such as image fusion
image stitching
long time sequence analysis etc.
and it is one of spotlights in the field of remote sensing information processing. High-precision registration of multi-temporal remote sensing images covering complex-terrain region is always a problem to break through. The conventional registration algorithms guiding by the transformation model
is enable to take the pixel-level geometric distortion into consideration
which means that the displacements of a pair of corresponding pixels is different from that of the other pair.
Under this circumstance
the global or local mapping function could not describe the geometric deformation between two images covering the complex-terrain region. Optical flow estimation calculates per-pixel displacements considering the very local distortions
even the pixel-level deformation in the computer vision field
providing a feasible and creative solution. It estimates displacement in x- and y-directions for a pair of corresponding pixels under the intensity and gradient consistency constraints
with resistant to the change of illumination. However
it is sensitive to land cover changes
which often lead to abnormal optical flow field and further affect the registered image after the coordinate transformation and resampling. To this end
a registration algorithm based on the optical flow modification for multi-temporal remote sensing images covering the complex-terrain region is proposed. On the preliminary optical flow field
Laplace of Gaussian operator is employed to detect the abnormal optical flow in Munsell color system. With the mask of abnormal optical flow based on the detection results
the Delaunay triangle curved surface interpolation is utilized to correct them
which is calculated by the around accurate pixel displacements. The coordinates in the sensed image are transformed
and the new pixel value is put on the corresponding pixel with the specified resampling method. Ultimately
the aligned image is generated. Experiments based on multi-temporal remote sensing images covering the complex-terrain region with land cover changes demonstrate that the proposed method achieves high-fidelity and high-precision registration compared with the results of the conventional methods.
Nevertheless
for registration of the image with sub-meter spatial resolution or image registration of different sensors
the difference of imaging angle
imaging mechanism
noise type etc. have an impact on the accuracy of the proposed algorithm. These remote sensing images are important data guarantee for fine research of earth surface and disaster assessment under poor imaging conditions in disaster region. How to realize high fidelity and high efficiency registration of the ultra-high resolution image or the multi-model image
is a problem that needs an in-depth study for us. In our future work
based on the proposed algorithm in this paper
research will be carried out specifically for the aforementioned problem. The aligned complex topographic region images will be applied to disaster monitoring
assessment
land use change analysis and other fields for an assessment to further improve our proposed method.
Bay H , Tuytelaars T and van Gool L . 2006 . SURF: Speeded up robust features // Proceedings of the 9th European Conference on Computer Vision . Graz, Austria : Springer : 404 - 417 [ DOI: 10.1007/11744023_32 http://dx.doi.org/10.1007/11744023_32 ]
Brigot G , Colin-Koeniguer E , Plyer A and Janez F . 2016 . Adaptation and evaluation of an optical flow method applied to coregistration of forest remote sensing images . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 9 ( 7 ): 2923 - 2939 [ DOI: 10.1109/JSTARS.2016.2578362 http://dx.doi.org/10.1109/JSTARS.2016.2578362 ]
Brox T , Bruhn A , Papenberg N and Weickert J . 2004 . High accuracy optical flow estimation based on a theory for warping // Proceedings of the 8th European Conference on Computer Vision . Prague, Czech Republic : Springer : 25 - 36 [ DOI: 10.1007/978-3-540-24673-2_3 http://dx.doi.org/10.1007/978-3-540-24673-2_3 ]
Cao S , Pan Y Z , Zhang J S and Yu Q Y . 2014 . Land cover patches based automatic multi-temporal remote sensing images registration . Acta Geodaetica et Cartographica Sinica , 43 ( 3 ): 290 - 297
曹森 , 潘耀忠 , 张锦水 , 喻秋艳 . 2014 . 土地覆盖图斑多时相遥感影像自动配准 . 测绘学报 , 43 ( 3 ): 290- 297 [ DOI: 10.13485/j.cnki.11-2089.2014.0042 http://dx.doi.org/10.13485/j.cnki.11-2089.2014.0042 ]
Chang H H , Wu G L and Chiang M H . 2019 . Remote sensing image registration based on modified SIFT and feature slope grouping . IEEE Geoscience and Remote Sensing Letters , 16 ( 9 ): 1363 - 1367 [ DOI: 10.1109/LGRS.2019.2899123 http://dx.doi.org/10.1109/LGRS.2019.2899123 ]
Chen X Y . 2009 . Image Registration Technology and MATLAB Programming . Beijing : Electronics Industry Press : 1 - 2
陈显毅 . 2009 . 图像配准技术及其MATLAB编程实现 . 北京 : 电子工业出版社 : 1 - 2
Ding L , Goshtasby A and Satter M . 2001 . Volume image registration by template matching . Image and Vision Computing , 19 ( 12 ): 821 - 832 [ DOI: 10.1016/S0262-8856(00)00101-3 http://dx.doi.org/10.1016/S0262-8856(00)00101-3 ]
Fan C , Gong J Y , Zhu J J and Zhang L H . 2008 . A sub-pixel registration approach of the ADS 40 images based on optical flow. Science of Surveying and Mapping , 33 ( 6 ): 13 - 15
范冲 , 龚健雅 , 朱建军 , 张立华 . 2008 . 基于光流的ADS40影像亚像素配准算法 . 测绘科学 , 33 ( 6 ): 13- 15 [ DOI: 10.3771/j.issn.1009-2307.2008.06.003 http://dx.doi.org/10.3771/j.issn.1009-2307.2008.06.003 ]
Feng R T , Li X H , Zou W L and Shen H F . 2017 . Registration of multitemporal GF-1 remote sensing images with weighting perspective transformation model // Proceedings of 2017 IEEE International Conference on Image Processing (ICIP) . Beijing, China : IEEE : 2264 - 2268 [ DOI: 10.1109/ICIP.2017.8296685 http://dx.doi.org/10.1109/ICIP.2017.8296685 ]
Feng R T , Du Q Y , Li X H and Shen H F . 2019 . Robust registration for remote sensing images by combining and localizing feature- and area-based methods . ISPRS Journal of Photogrammetry and Remote Sensing , 151 : 15 - 26 [ DOI: 10.1016/j.isprsjprs.2019.03.002 http://dx.doi.org/10.1016/j.isprsjprs.2019.03.002 ]
Gong M G , Zhao S M , Jiao L C , Tian D Y and Wang S . 2014 . A novel coarse-to-fine scheme for automatic image registration based on SIFT and mutual information . IEEE Transactions on Geoscience and Remote Sensing , 52 ( 7 ): 4328 - 4338 [ DOI: 10.1109/TGRS.2013.2281391 http://dx.doi.org/10.1109/TGRS.2013.2281391 ]
Goshtasby A . 1986 . Piecewise linear mapping functions for image registration . Pattern Recognition , 19 ( 6 ): 459 - 466 [ DOI: 10.1016/0031-3203(86)90044-0 http://dx.doi.org/10.1016/0031-3203(86)90044-0 ]
Goshtasby A . 1988 . Registration of images with geometric distortions . IEEE Transactions on Geoscience and Remote Sensing , 26 ( 1 ): 60 - 64 [ DOI: 10.1109/36.3000 http://dx.doi.org/10.1109/36.3000 ]
Guan X B , Shen H F , Gan W X and Zhang L P . 2015 . Estimation and spatiotemporal analysis of winter NPP in Wuhan based on Landsat TM/ETM+ Images . Remote Sensing Technology and Application , 30 ( 5 ): 884 - 890
管小彬 , 沈焕锋 , 甘文霞 , 张良培 . 2015 . 基于Landsat TM/ETM+影像的武汉市冬季NPP估算及其时空变化分析 . 遥感技术与应用 , 30 ( 5 ): 884- 890 [ DOI: 10.11873/j.issn.1004-0323.2015.5.0884 http://dx.doi.org/10.11873/j.issn.1004-0323.2015.5.0884 ]
Harris C and Stephens M . 1988 . A combined corner and edge detector // Proceedings of the 4th Alvey Vision Conference . Manchester, UK : Alvey Vision Club : 263 - 284 [ DOI: 10.5244/C.2.23 http://dx.doi.org/10.5244/C.2.23 ]
He M M , Guo Q , Li A , Chen J , Chen B and Feng X X . 2018 . Automatic fast feature-level image registration for high-resolution remote sensing images . Journal of Remote Sensing , 22 ( 2 ): 277 - 292
何梦梦 , 郭擎 , 李安 , 陈俊 , 陈勃 , 冯旭祥 . 2018 . 特征级高分辨率遥感图像快速自动配准 . 遥感学报 , 22 ( 2 ): 277- 292 [ DOI: 10.11834/jrs.20186420 http://dx.doi.org/10.11834/jrs.20186420 ]
Horn B K P and Schunck B G . 1981 . Determining optical flow . Artificial Intelligence , 17 ( 1/3 ): 185 - 203 [ DOI: 10.1016/0004-3702(81)90024-2 http://dx.doi.org/10.1016/0004-3702(81)90024-2 ]
Kupfer B , Netanyahu N S and Shimshoni I . 2015 . An efficient SIFT-based mode-seeking algorithm for sub-pixel registration of remotely sensed images . IEEE Geoscience and Remote Sensing Letters , 12 ( 2 ): 379 - 383 [ DOI: 10.1109/LGRS.2014.2343471 http://dx.doi.org/10.1109/LGRS.2014.2343471 ]
Li X H , Hui N , Shen H F , Fu Y J and Zhang L P . 2015 . A robust mosaicking procedure for high spatial resolution remote sensing images . ISPRS Journal of Photogrammetry and Remote Sensing , 109 : 108 - 125 [ DOI: 10.1016/j.isprsjprs.2015.09.009 http://dx.doi.org/10.1016/j.isprsjprs.2015.09.009 ]
Lin X F , Lin L W and Deng T . 2010 . Remote sensing image registration based on SURF descriptor . Computer Engineering , 36 ( 12 ): 216 - 218
林晓帆 , 林立文 , 邓涛 . 2010 . 基于SURF描述子的遥感影像配准 . 计算机工程 , 36 ( 12 ): 216- 218 [ DOI: 10.3969/j.issn.1000-3428.2010.12.074 http://dx.doi.org/10.3969/j.issn.1000-3428.2010.12.074 ]
Lindeberg T . 1998 . Feature detection with automatic scale selection . International Journal of Computer Vision , 30 ( 2 ): 79 - 116 [ DOI: 10.1023/A:1008045108935 http://dx.doi.org/10.1023/A:1008045108935 ]
Liu G X and Wang L . 2007 . An image registration method based on region selecting and feature points matching . Journal of Optoelectronics·Laser , 18 ( 8 ): 999 - 1002
刘贵喜 , 王蕾 . 2007 . 基于区域选择和特征点匹配的图像配准算法 . 光电子·激光 , 18 ( 8 ): 999- 1002 [ DOI: 10.3321/j.issn:1005-0086.2007.08.031 http://dx.doi.org/10.3321/j.issn:1005-0086.2007.08.031 ]
Liu L , Chen F and Liu J B . 2014 . Optical flow and feature constrains algorithm for remote sensing image registration . Computer Engineering and Design , 35 ( 9 ): 3127 - 3131
刘璐 , 陈甫 , 刘建波 . 2014 . 基于特征约束与光流场方法的遥感图像配准 . 计算机工程与设计 , 35 ( 9 ): 3127- 3131 [ DOI: 10.3969/j.issn.1000-7024.2014.09.030 http://dx.doi.org/10.3969/j.issn.1000-7024.2014.09.030 ]
Lowe D G . 2004 . Distinctive image features from scale-invariant keypoints . International Journal of Computer Vision , 60 ( 2 ): 91 - 110 [ DOI: 10.1023/B:VISI.0000029664.99615.94 http://dx.doi.org/10.1023/B:VISI.0000029664.99615.94 ]
Lv J J , Wen G J , Li D R and Gao F . 2007 . An automated image registration method based on corner feature . Remote Sensing Technology and Application , 22 ( 3 ): 438 - 442
吕金建 , 文贡坚 , 李德仁 , 高峰 . 2007 . 一种基于角点特征的图像自动配准方法 . 遥感技术与应用 , 22 ( 3 ): 438- 442 [ DOI: 10.11873/j.issn.1004-0323.2007.3.438 http://dx.doi.org/10.11873/j.issn.1004-0323.2007.3.438 ]
Ma W P , Zhang J , Wu Y , Jiao L C , Zhu H and Zhao W . 2019 . A novel two-step registration method for remote sensing images based on deep and local features . IEEE Transactions on Geoscience and Remote Sensing , 57 ( 7 ): 4834 - 4843 [ DOI: 10.1109/TGRS.2019.2893310 http://dx.doi.org/10.1109/TGRS.2019.2893310 ]
Murphy J M , Le Moigne J and Harding D J . 2016 . Automatic image registration of multimodal remotely sensed data with global shearlet features . IEEE Transactions on Geoscience and Remote Sensing , 54 ( 3 ): 1685 - 1704 [ DOI: 10.1109/TGRS.2015.2487457 http://dx.doi.org/10.1109/TGRS.2015.2487457 ]
Nagarajan S and Schenk T . 2016 . Feature-based registration of historical aerial images by Area Minimization . ISPRS Journal of Photogrammetry and Remote Sensing , 116 : 15 - 23 [ DOI: 10.1016/j.isprsjprs.2016.02.012 http://dx.doi.org/10.1016/j.isprsjprs.2016.02.012 ]
Sedaghat A and Mohammadi N . 2019 . High-resolution image registration based on improved SURF detector and localized GTM . International Journal of Remote Sensing , 40 ( 7 ): 2576 - 2601 [ DOI: 10.1080/01431161.2018.1528402 http://dx.doi.org/10.1080/01431161.2018.1528402 ]
Shen H F , Meng X C and Zhang L P . 2016 . An integrated framework for the spatio-temporal-spectral fusion of remote sensing images . IEEE Transactions on Geoscience and Remote Sensing , 54 ( 12 ): 7135 - 7148 [ DOI: 10.1109/TGRS.2016.2596290 http://dx.doi.org/10.1109/TGRS.2016.2596290 ]
Tang Y , Wang L J , Ma G C , Jia H J and Jin X . 2019 . Emergency monitoring of high-level landslide disasters in Jinsha River using domestic remote sensing satellites . Journal of Remote Sensing , 23 ( 2 ): 252 - 261
唐尧 , 王立娟 , 马国超 , 贾虎军 , 靳晓 . 2019 . 利用国产遥感卫星进行金沙江高位滑坡灾害灾情应急监测 . 遥感学报 , 23 ( 2 ): 252- 261 [ DOI: 10.11834/jrs.20198405 http://dx.doi.org/10.11834/jrs.20198405 ]
Wang H X , Jin H J , Lei C Q , Jiang W S and Wang Y . 2015 . A visually inspired variational method for automatic image registration . Acta Geodaetica et Cartographica Sinica , 44 ( 8 ): 893 - 899
王慧贤 , 靳惠佳 , 雷呈强 , 江万寿 , 王艳 . 2015 . 视觉驱动的变分配准方法 . 测绘学报 , 44 ( 8 ): 893- 899 [ DOI: 10.11947/j.AGCS.2015.20140281 http://dx.doi.org/10.11947/j.AGCS.2015.20140281 ]
Watson D F and Philip G M . 1984 . Triangle based interpolation . Journal of the International Association for Mathematical Geology , 16 ( 8 ): 779 - 795 [ DOI: 10.1007/BF01036704 http://dx.doi.org/10.1007/BF01036704 ]
Wong A and Clausi D A . 2007 . ARRSI: automatic registration of remote-sensing images . IEEE Transactions on Geoscience and Remote Sensing , 45 ( 5 ): 1483 - 1493 [ DOI: 10.1109/TGRS.2007.892601 http://dx.doi.org/10.1109/TGRS.2007.892601 ]
Wu X X . 2010 . Image registration algorithm based on template matching and optical flow . Journal of Wuxi Institute of Technology , 9 ( 6 ): 43 - 45
吴迅兮 . 2010 . 基于模板匹配和光流法的图像配准方法 . 无锡职业技术学院学报 , 9 ( 6 ): 43- 45 [ DOI: 10.3969/j.issn.1671-7880.2010.06.014 http://dx.doi.org/10.3969/j.issn.1671-7880.2010.06.014 ]
Zagorchev L and Goshtasby A . 2006 . A comparative study of transformation functions for nonrigid image registration . IEEE Transactions on Image Processing , 15 ( 3 ): 529 - 538 [ DOI: 10.1109/TIP.2005.863114 http://dx.doi.org/10.1109/TIP.2005.863114 ]
Zhang Q , Cao Z G , Hu Z W , Jia Y H and Wu X L . 2015 . Joint image registration and fusion for panchromatic and multispectral images . IEEE Geoscience and Remote Sensing Letters , 12 ( 3 ): 467 - 471 [ DOI: 10.1109/LGRS.2014.2346398 http://dx.doi.org/10.1109/LGRS.2014.2346398 ]
Zhang Q , Liu Z K , Pang Y W and Li W . 2003 . Automatic registration of aerophotos based on SUSAN operator . Acta Geodaetica et Cartographica Sinica , 32 ( 3 ): 245 - 250
张迁 , 刘政凯 , 庞彦伟 , 李威 . 2003 . 基于SUSAN算法的航空影像的自动配准 . 测绘学报 , 32 ( 3 ): 245- 250 [ DOI: 10.3321/j.issn:1001-1595.2003.03.012 http://dx.doi.org/10.3321/j.issn:1001-1595.2003.03.012 ]
Zhu Z W , Shen Z F and Luo J C . 2011 . Parallel remote sensing image registration based on improved SIFT point feature . Journal of Remote Sensing , 15 ( 5 ): 1024 - 1039
朱志文 , 沈占锋 , 骆剑承 . 2011 . 改进SIFT点特征的并行遥感影像配准 . 遥感学报 , 15 ( 5 ): 1024- 1039 [ DOI: 10.11834/jrs.20110216 http://dx.doi.org/10.11834/jrs.20110216 ]
相关文章
相关作者
相关机构
京公网安备11010802024621