基于邻域总变分和势直方图函数的高分辨率遥感影像建筑物提取  

Building extraction from high-resolution remotely sensed imagery based on neighborhood total variation and potential histogram function

作　　者：施文灶[1,2,3] 刘金清[1,2,3] 

机构地区：[1]福建师范大学光电与信息工程学院,福州350108 [2]福建师范大学医学光电科学与技术教育部重点实验室,福州350007 [3]福建师范大学福建省光子技术重点实验室,福州350007

出　　处：《计算机应用》2017年第6期1787-1792,共6页journal of Computer Applications

基　　金：教育部"长江学者和创新团队发展计划"创新团队项目滚动支持计划(IRT_15R10);福建省自然科学基金项目(2017J01464)~~

摘　　要：针对现在的高分辨率遥感影像建筑物识别与提取方法存在的准确率低及数据要求严格等问题,提出一种基于邻域总变分(NTV)和势直方图函数(PHF)的方法。首先,计算遥感影像各像元的加权邻域总变分似然函数取值,并进行区域生长分割,将矩形度和长宽比作为约束条件提取候选建筑物;然后,进行阴影自动提取;最后,利用数学形态学对阴影进行处理,计算处理后的阴影和候选建筑物之间的邻接关系得到建筑物,并用最小外接矩形对其边界进行拟合。为了验证所提算法的有效性,选取深圳市PLEIADES影像中9幅具有代表性的子影像进行实验。实验结果表明,所提方法的平均查准率和平均查全率分别达到97.71%和84.21%,与水平集和基于颜色不变性特征两种建筑物提取方法相比,在总体性能F_1上具有10%以上的提高。Concerning the problems of the low accuracy and high requirements for data in the existing building identification and extraction methods from high-resolution remotely sensed imagery, a new method based on Neighborhood Total Variation （NTV） and Potential Histogram Function （PHF） was proposed. Firstly, the value of weighted NTV likelihood function for each pixel of a remotely sensed imagery was calculated, the segmentation was done with region growing method, and the candidate buildings were selected from the segmentation results with the constraints of rectangular degree and aspect ratio. Then, the shadows were detected automatically. At last, shadows were processed with morphology operations. The buildings were extracted by computing the adjacency relationship of the processed shadows and candidate buildings, and the building boundaries were fitted with the minimum enclosing rectangle. For verifying the validity of the proposed method, nine representative sub-images were chosen from PLEIADES images covering Shenzhen for experiment. The experimental results show that, the average precision and recall of the proposed method are 97.71% and 84.21% for the object-based evaluation, and the proposed method has increased the overall performance F1 by more than 10% compared with two other building extraction methods based on level set and color invariant feature.

关 键 词：高分辨率遥感影像 势直方图函数 邻域总变分 形态学 建筑物提取 

分 类 号：P407.8[天文地球—大气科学及气象学]