电子学报2012，Vol.40Issue(6)：1141-1147,7.DOI:10.3969/j.issn.0372-2112.2012.06.012
基于改进Markov随机场的高分辨率SAR图像建筑物分割算法
Building Segmentation from High-Resolution SAR Images Based on Improved Markov Random Field
摘要
Abstract
An approach was proposed for building segmentation from high resolution SAR (Synthetic Aperture Radar) images based on an improved Markov random field (MRF) model. Aiming at the property of low SNR (Signal to Noise Ratio) of SAR images and the complexity of building textures, we obtained the initial segmentation using the maximum likelihood (ML) algorithm based on the multi-scale MRF model and involved the Gabor similarity between pixels based on the traditional MRF potential function,and employed the ICM (Iterative Conditional Model) algorithm to implement the segmentation.The experimental results on several real SAR images show that the proposed approach performs better than traditional methods in the segmentation accuracy, and building boundaries are clearly obtained by the proposed approach.关键词
高分辨率SAR图像/建筑物分割/多尺度Markov随机场/Gabor特征Key words
high-resolution SAR image/ building segmentation/ multi- scale Markov model/ Gabor feature分类
信息技术与安全科学引用本文复制引用
傅兴玉,尤红建,付琨..基于改进Markov随机场的高分辨率SAR图像建筑物分割算法[J].电子学报,2012,40(6):1141-1147,7.基金项目
国家自然科学基金(No.40871209) （No.40871209）
