基于向量场模型的多光谱遥感图像多尺度边缘检测  

Multiscale Edge Detection in Multispectral Remotely Sensed Imagery Based on Vector Field Model

作　　者：李晖[1] 肖鹏峰[1] 冯学智[1] 冯莉[2] 王珂[1] 

机构地区：[1]南京大学地理与海洋科学学院,江苏南京210093 [2]斯图加特大学区域发展规划研究所,斯图加特70569

出　　处：《测绘学报》2012年第1期100-107,共8页Acta Geodaetica et Cartographica Sinica

基　　金：国家863计划(2008AA12Z106);国家自然科学基金(40801166);高等学校博士学科点专项科研基金(200802841012)

摘　　要：提出一种基于向量场模型的多光谱图像多尺度边缘检测算法,并在算法中引入两种梯度方向量化邻域模型。首先,对多光谱图像进行二进小波变换,得到每个波段图像在不同尺度上的细节系数,然后根据向量场模型计算多光谱图像的梯度幅值和梯度方向,选择适宜的邻域模型对梯度方向进行量化,最后沿量化后的方向获取由细到粗的多层次边缘信息。对QuickBird多光谱图像上农田、厂房等地物进行多尺度边缘提取,定性分析图像分辨率大小与地物尺寸关系在不同尺度边缘信息的表征;利用F测度,定量评价检测结果的边缘准确度。与传统算子检测结果对比表明,利用向量场模型综合所有波段的边缘信息,减少多波段图像边缘信息的不一致性,引入的量化邻域模型能够有效地获取完整的多尺度边缘点。A novel algorithm to detect the multi-scale edge features on multispectral remotely sensed imagery was proposed, and two different neighborhood models in the algorithm was introduced to lead to locate edge points more complete. Firstly, multispectral images are defined by using of the vector field model. And then the dyadic wavelet transform is applied to produce the multi-scale edge detail coefficients, and first fundamental form is used for detecting the gradient magnitude and orientation of multispectral images at different levels. Lastly, edge points are located along with the quantified orientation of gradient by using the optimal neighborhood model at different scales. A variety of experiments by using QuickBird multispectral images of Nanjing area were presented to demonstrate the representation efficient. It is shown from the results that the edge information of the objects, i.e. factory, paddy, can be detected clearly from coarse to fine at different scale levels. The relationship of the size of the ground features between the spatial resolution of image was analyzed and to try to find a suitable level to demonstrate the feature of different objects. And the local maximum of the gradient magnitude provides information of the image edge feature which can be detected from the gradient modulus along with the quantified gradient orientation. Quantification of the gradient orientation should consider the direction of objects in the image. Using F-measure, the results by the proposed method has higher precision than the traditional edge detectors.

关 键 词：多光谱遥感图像 边缘检测 多尺度 向量场 二进小波变换 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]