基于L_(1)范数混合主动轮廓的河流SAR图像分割  

River SAR image segmentation using L_(1) norm based hybrid active contours

作　　者：邢一波 韩斌 鲍秉坤 XING Yibo;HAN Bin;BAO Bingkun(School of Communications and Information Engineering,Nanjing University of Posts and Telecommunications,Nanjing 210003,China;School of Computer Science,Nanjing University of Posts and Telecommunications,Nanjing 210023,China)

机构地区：[1]南京邮电大学通信与信息工程学院,江苏南京210003 [2]南京邮电大学计算机学院,江苏南京210023

出　　处：《测绘学报》2024年第8期1598-1609,共12页Acta Geodaetica et Cartographica Sinica

基　　金：国家自然科学基金(62325206,61936005,62201281);江苏省自然科学基金(BK20220392);南京邮电大学引进人才自然科学研究启动基金(NY222004)。

摘　　要：为解决现有主动轮廓模型难以准确分割河流SAR图像的问题,提出一种基于L_(1)范数的混合主动轮廓模型。首先,计算轮廓曲线内外区域像素灰度的中值作为区域拟合中心,以抑制SAR图像中干扰区域对其准确性的影响;然后,利用L_(1)范数构建新的能量约束项并在模型能量泛函中引入边缘指示函数,进一步提升模型的分割性能;最后,将基于L_(1)范数的中值和均值能量约束项结合起来并添加额外的区域拟合中心约束项,以提高模型的整体稳定性。针对实际河流SAR图像进行分割试验,结果表明,与现有分割方法相比,本文模型能更准确、稳定地分割河流SAR图像。To solve the problem that the existing active contour models are difficult to segment river SAR images accurately,this paper presents a hybrid active contour model based on the L_(1) norm.First,the median values of the pixel intensities in the inner and outer regions of the contour curve are calculated as the region fitting centers to suppress the influence of the interference regions in SAR images on their accuracies.Second,the L_(1) norm is used to construct a new energy constraint term and the edge indicator function is introduced into the model's energy functional to further enhance the segmentation performance.Finally,the median and mean energy constraint terms based on the L_(1) norm are combined and additional region-fitting center constraint terms are added to improve the overall stability of the model.The segmentation experiments on real river SAR images show that the proposed model can segment river SAR images more accurately and stably than the existing models.

关 键 词：河流分割 SAR图像 主动轮廓模型 混合能量项 L_(1)范数 

分 类 号：P237[天文地球—摄影测量与遥感]