Matching SAR image to optical image using modified Hausdorff distance and genetic algorithms

Haicen Mao; Qiuze Yu; Tianxu Zhang

doi:10.1117/12.750623

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15 November 2007 Matching SAR image to optical image using modified Hausdorff distance and genetic algorithms

Haicen Mao; Qiuze Yu; Tianxu Zhang

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Proceedings Volume 6788, MIPPR 2007: Pattern Recognition and Computer Vision; 678820 (2007) https://doi.org/10.1117/12.750623
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

A novel algorithm for matching synthetic aperture radar (SAR) image to Optical image based on lineal feature using Hausdorff distance combined with genetic algorithm is proposed in this paper. A new method is presented to extract lineal feature from low signal to noise ratio (SNR) SAR image. Based on the edge image from SAR and Optical image, modified Hausdorff distance is adopted as a similarity measure because it is insensitive to noise. Genetic algorithm is used as searching strategy to achieve high computation speed for its inertial parallel. Experimental results using real SAR and Optical images demonstrate that the algorithm is robust, fast and can achieve high matching accuracy.

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Haicen Mao, Qiuze Yu, and Tianxu Zhang "Matching SAR image to optical image using modified Hausdorff distance and genetic algorithms", Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 678820 (15 November 2007); https://doi.org/10.1117/12.750623