基于无人机遥感影像的水体提取方法  

Water extraction from unmanned aerial vehicle remote sensing images

作　　者：卞艳[1] 宫雨生[1] 马国鹏 王昶[1] BIAN Yan;GONG Yu-sheng;MA Guo-peng;WANG Chang(School of Civil Engineering,University of Science and Technology Liaoning,Anshan 114051,China)

机构地区：[1]辽宁科技大学土木工程学院,辽宁鞍山114051

出　　处：《浙江大学学报（工学版）》2022年第4期764-774,共11页Journal of Zhejiang University：Engineering Science

基　　金：国家自然科学基金青年科学基金资助项目(41801294);武汉大学测绘遥感信息工程国家重点实验室珞珈一号特别开放研究基金资助项目(18T07)。

摘　　要：针对无人机(UAV)影像水体提取出现的噪声干扰、光谱混淆、分割尺度难把握、无法使用水体指数等问题,提出边缘检测算法结合面向对象方法的新水体提取方法(AUCSN).采用各向扩散滤波算法对影像去噪;采用Canny边缘检测算子对去噪后影像进行边缘提取,提取结果与去噪后影像进行波段重组,利用改进的邻域绝对均值差分方差比法对重组影像选取最优分割尺度,开展多尺度分割.结合水体对象的光谱、形态、纹理特征建立模型,对分割后影像实现水体粗提取.将粗提取结果利用形态学闭运算填充孔洞,实现水体提取.实验结果表明,采用AUCSN方法进行水体提取,不仅提高了提取效率,而且提取精度能够达到96%.A new method named automatic segmentation(AUCSN),which combines edge detection algorithm with the object-oriented method,was proposed in order to solve the problems such as noise interference,spectral confusion,segmentation scale error,and water index unavailable which happen in water extraction from unmanned aerial vehicle(UAV)images.An anisotropic diffusion filtering algorithm was used to denoise the image.The Canny edge detection operator was used to extract the edge of the denoised image,and the extraction results were reconstructed with the denoised image.Then an improved absolute mean difference variance ratio method was used to select the optimal segmentation scale for the reconstructed image to conduct multi-scale segmentation.A model combined with the spectral,morphological,and texture feature of the water object was established in order to coarsely extract water objects from the segmented image.The morphological closed operation was used to fill the holes of the coarse extraction results,realizing water extraction.Results show that the AUCSN method can improve the extraction efficiency and the extraction accuracy can reach 96%.

关 键 词：无人机影像 去噪 CANNY 多尺度分割 特征提取 形态学 

分 类 号：TP75[自动化与计算机技术—检测技术与自动化装置]