几何特征表达及基于几何特征的建筑物提取

Geometric Feature Representation and Building Extraction Based on Geometric Features

通过分析高分辨率遥感图像中建筑物光谱特征存在严重的"同物异谱"和"同谱异物"等情况,发现建筑物的几何特征比其光谱特征更加典型.在总结了建筑物的一些典型几何特征之后,进行了基于几何特征(面积特征、矩形拟合度特征、长宽比特征、走向特征)的建筑物提取实验,发现利用几何特征能够比较有效地提取到建筑物.由于图像分割离不开光谱特征,即建筑物几何特征的计算受到其光谱特征的影响,依据几何特征的建筑物提取结果不是非常令人满意的.高度特征是建筑物最典型的几何特征之一,因此将高度特征引入到图像分割和建筑物提取过程是提高建筑物提取精度的新方向.

Problems exist in building extraction from high-resolution remote sensing images in terms of spectral features. For example, the same object has different spectra and different objects have the same spectrum, and geometric features of a building may be more typical than its spectral features. Having summarized some typical geometric features of buildings, building extraction is done based on their geometric features with features of area, fitting rectangle, length-to-width ratio, and main directions. The experiment shows that extracting buildings with geometric features is more effective than with spectral features. However, since image segmentation depends on spectral features so that calculation of geometric features is affected by spectral features, building extraction based on geometric features is not satisfactory. As the height feature of a building is the most typical geometry features, introduction of height features into image segmentation and feature extraction is an effective way to improve accuracy of building extraction.