Computer Science ›› 2017, Vol. 44 ›› Issue (7): 283-288.doi: 10.11896/j.issn.1002-137X.2017.07.051

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Fast and Robust SAR Image Matching Algorithm

WU Peng, YU Qiu-ze and MIN Shun-xin   

  • Online:2018-11-13 Published:2018-11-13

Abstract: To solve the problem that SIFT and its improved algorithm have low matching performance(poor university,low matching accuracy,high time complexity)in the multi-band SAR image matching,we improved the algorithm respectively from creating scale space and descriptors within the framework of the SIFT algorithm.In scale space level,we proposed to use gauss guided filter to construct scale space and use bilateral filter in image pre-processing stage.This strategy,efficient filter speckles noise and keeps the image’s information,makes full use of gauss guided filter real-time and rotational symmetry and the edge preserving advantages of bilateral filter.In the construction descriptor stage,in order to ensure the distinction and reduce the time of build descriptors,we adopted the local difference binary to describing the local features’ characteristics.In the matching stage,the coarse matching uses the algorithm of nearest neighbor firstly,and then the sparse vector field consensus is used to remove the error matching points quickly.The experimental results show that the proposed algorithm from SAR image matching on time complexity and the matching probability is better than the BFSIFT and KAZE algorithm.In conclusion,our proposed algorithm is an efficient algorithm of real-time,robustness and high matching probability.

Key words: SAR image match,Scale space,Bilateral filter,Guided filter,LDB,VFC

[1] LOWE D G.Distinctive image features from scale-invariant keypoints[J].International Journal of Computer Vision,2004,60(2):91-110.
[2] LINDEBERG T.Scale space theory:A basic tool for analyzing structures at different scales[J].International Journal of Computer Vision,2000,37(2):151-172.
[3] WANG S H,YOU H J,FU K.BFSIFT:A novel method to find feature matches for SAR image registration[J].IEEE Geo-science and Remote Sensing Letters,2012,9(4):649-653.
[4] TOMASI C,MANDUCHI R.Bilateral Filtering for Gray and Color Images[C]∥IEEE International Conference on Computer Vision.1998:839-846.
[5] FAN J W,WU Y,WANG F,et al.SAR Image Registration Using Phase Congruency and Nonlinear Diffusion-Based SIFT[J].IEEE Geoscience and Remote Sensing Letters,2015,12(3):562-566.
[6] ALCANTARILLA P F,BARTOLI A,DAVISON A J.KAZE Features[C]∥European Conference on Computer Vision(ECCV).Fiorenze,Italy,Springer,2012:214-227.
[7] ALCANTARILLA P F,NUEVO J,BARTOLI A.Fast Explicit Diffusion for Accelerated Features in Nonlinear Scale Spaces[C]∥British Machine Vision Conference(BMVC).Bristol,UK,2013:1-11.
[8] ZHANG Z Q,WANG W Y.A modify bilateral filtering algorithm[J].Journal of Image and Graphics,2009,14(3):443-447.(in Chinese) 张志强,王万玉.一种改进的双边滤波算法[J].中国图像图形学报,2009,14(3):443-447 .
[9] MIKOLAJCZYK K,SCHMID C.A performance evaluation of local descriptors[J].IEEE Transactions Pattern Analysis Machine Intelligence,2005,27(10):1615-1630.
[10] KE Y,SUKTHANKAR R.PCA-SIFT:A More Distinctive Representation for Local Image Descriptors[C]∥Computer Vision and Pattern Recognition(CVPR).2004:506-513.
[11] BAY H,ESS A,TUYTELAARS T, GOOL L V.Speed-Up Robust Features(SURF)[J].Computer Vision and Image Understanding,2008,110(3):346-359.
[12] TOLA E,LEPETIT V,FUA P.DAISY:An Efficient Dense Descriptor Applied to Wide-Baseline Stereo[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2009,32(5):815-830.
[13] CALONDER M,LEPETIT V,OZUYSAL M,et al.BRIEF:computing a local binary very fast[J].IEEE Translations on Pattern Analysis and Matchine Intelligence,2012,34(7):1281-1298.
[14] RUBLEE E,RABAUD V,KONOLIGE K,et al.ORB:an effi-cient alternative to SIFT or SURF[C]∥Proceedings of International Conference on Computer Vision.Barcelona,Spain,2011:2564-2571.
[15] LEUTENEGGER S,CHLI M,SIEGWART R Y.BRISK:Binary robust invariant scalable keypoints[C]∥ IEEE International Conference on Computer Vision.2011:2548-2555.
[16] YANG X,CHENG K T.Local Difference Binary for Ultrafast and Distinctive Feature Description[J].IEEE Transactions on Pattern Analysis and Matchine Intelligence,2013,35(1):188-194.
[17] ZHAO J,MA J Y,TIAN J W,et al.A robust method for vector field learning with application to mismatch removing[C]∥IEEE International Conference on Computer Vision and Pattern Re-cognition.New York,IEEE,2011:2977-2984.
[18] HE K M,SUN J,TANG X O.Guided Image Filtering[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2014,35(6):1397-1409.
[19] LEE J S,HOPPEL K,MANGO S A.Unsupervised estimation of speckle noise in radar images[J].International Journal of Imaging Systems and Technology,1992,4(4):298-305.
[20] HAN C M,GUO H D,WANG C L,et al.Edge- Preserving Filter for SAR Images[J].High Technology Letters,2003,13(7):11-15.(in Chinese) 韩春明,郭华东,王长林,等.保持边缘的SAR图像滤波方法[J].高技术通讯,2003,13(7):11-15.
[21] PERPNA P,MALIK J.Scale space and edge detection using anisotropic diffusion[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1990,12(7):629-639.
[22] DELLINGER F,DELON J,GOUSSEAU Y,et al.SAR-SIFT:A SIFT-Like Algorithm for SAR Images[J].IEEE Transactions on Geoscience and Remote Sensing,2015,53(1):453-466.

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