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中文摘要：
利用灰度共生矩阵提取SAR影像的纹理特征,分析灰度共生矩阵的原理、特征向量以及特征参数的确定。利用对数比值算子构造差异影像,通过比较发现基于反差的差异影像更能突出变化信息。选择基于反差的差异影像作为变化检测的基准,由于其影像符合高斯混合模型,利用期望最大（EM）算法对高斯混合模型进行参数估计。最后利用贝叶斯最小错误率进行变化信息的提取,与基于像元灰度值的变化检测结果进行比较,试验证明基于灰度共生矩阵纹理特征的变化检测方法虚警率更低、漏检率更低、总体误差更小,具有更好的检测效果。
英文摘要：
The authors found difference images based on the contrast can stand out changed information better using texture features extraction of SAR images based on gray level co-ocurrence matrix,to analyze the principle of the GLCM,feature vectors and the characteristic parameters determined,logarithmic ratio operator constructed difference images,we made the difference images based on the contrast as the base of change detection.As the images in accordance with the Gaussian mixture model,so we estimate the parameters of the Gaussian mixture model with expectation maximum（EM） algorithm,and then use Bayesian minimum error rate to extract change information,finally compare it with the change detection results based on the pixel grayscale value.The test proved that the change detection method based on GLCM texture features has the lower false alarm rate,the lower missing rate,the smaller overall error and better detection effect.
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