梯度幅度法提取探地雷达图像ROI  

Gradient Method to Extract ROI of GPR Image

作　　者：金淼[1] 赵永辉[1] 吴健生[1] 谢雄耀[2] 

机构地区：[1]同济大学海洋与地球科学学院,上海200092 [2]同济大学地下建筑与工程系,上海200092

出　　处：《中国图象图形学报》2009年第4期579-584,共6页Journal of Image and Graphics

基　　金：国家自然科学基金项目(40704023);浙江省自然科学基金项目(Y506286)

摘　　要：探地雷达图像中双曲型回波特征是识别地下管线的重要依据。根据探地雷达图像具有子波频率信息的特殊性,提出了一种基于梯度幅度的ROI(感兴趣区域)自动提取新方法。通过优化梯度幅度图的微分取值方式,使梯度幅度图中的双曲型特征更为突出;以直方图方式分析灰度信息分布,并自动求取阈值,以该阈值对梯度幅度图进行二值化处理;在此基础上,采用连通区域算法对特征区域进行扩充分割,并根据区域面积剔除杂波区域,从而提取出探地雷达图像中双曲型回波的ROI区域。该方法计算速度快、准确度高,易于在实际探测中实现。The hyperbolic echo feature in Ground Penetrating Radar（GPR） image is one of the most important basis for pipelines recognition. According to the GPR image＇ s wavelet spectrum information,this paper presents a new ROI extraction method based on GPR gradient image. First for highlighting the hyperbolic echo regions and suppressing the background region in GPR image better, we revise the differential parameter of obtaining the GPR gradient image. Then we use the histogram to get the threshold value for the binarization process to the gradient image. After the binary gradient image is expanded, the connected region detecting algorithm is selected for region division. At last, small area regions are eliminated as clutter regions. Then the hyperbolic echo regions are extracted from GPR image. This new ROI extraction method has high calculate speed and accuracy, and is easy to be realized in actual detection analysis.

关 键 词：梯度幅度图 探地雷达 ROI提取 双曲型特征 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]