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《Acta Geodaetica et Cartographica Sinica》 2010-06
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Multi-source Remote Sensing Image Matching Based on Contourlet-domain Hausdorff Distance and Particle Swarm Optimization

CHEN Sa,WU Yiquan School of Information Science and Technology,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China  
To further improve the accuracy and efficiency of multi-source remote sensing image matching,an algorithm based on contourlet transform,Hausdorff distance and improved particle swarm optimization was proposed in this paper.Firstly,the target image and reference image were decomposed to the low resolution image using contourlet transform.Then,wavelet modulus maxima algorithm was employed to extract the edges in the low-frequency subbands,and least-trimmed-squares Hausdorff distance(LTS-HD) was used as similarity measure for image matching.Meanwhile,the extremum disturbed and simple particle swarm optimization was introduced to get the rough matching results.The position of rough matching results was corresponded to the original image and then the matching between the higher resolution images could be implemented stepwise up to the full resolution images.The experimental results show that,compared with those of other common sensing image matching methods,the proposed algorithm has the high accuracy,efficiency and strong robustness.
【Fund】: 国家自然科学基金(60872065)
【CateGory Index】: TP751
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