基于小波纹理和基元合并的高分影像居民地提取

Extraction of residential area from high resolution images based on wavelet texture and primitive merging

由于高分辨率全色影像(简称"高分影像")中的信息高度细节化,再加上噪声的影响,会导致传统基于纹理特征的居民地提取方法效果不理想。为此,提出一种基于小波纹理和基元合并的居民地提取方法。首先,利用结合小波变换(wavelet transform,WT)的分形网络进化算法(fractal net evolution approach,FNEA)获取初始基元,并对基元的多尺度小波纹理进行分析;然后,在人工给定种子基元的基础上合并具有相似纹理的基元;最后,对基元合并的结果进行数学形态学修整,得到居民地区域。利用天绘一号(TH-1)全色影像对所提方法进行验证及对比分析的结果表明,该方法对高分影像中的街区式居民地可取得较高的提取精度和计算效率。

Due to the highly detailed information and noise in the high resolution panchromatic images, the results of traditional residential area extraction algorithms based on texture features are not satisfactory. To tackle this problem, the authors propose a method based on wavelet texture and primitive merging in this paper. For obtaining the initial primitives, the image was firstly segmented by fractal net evolution approach modified by the wavelet transform, and then the multi - scale wavelet texture features extraction method was directly applied to the irregular image primitives. Based on the artificially provided seed primitives, the algorithm merged the primitives with similar texture features and then applied morphological methods to the result of primitive merging. In the experiment, Mapping Satellite - 1 （ TH - 1 ） panchromatic images were used to validate the proposed method. The comparative analysis with other texture features - based methods shows that the proposed method could extract the street - block residential area from high resolution panchromatic images with a higher extraction accuracy and computational efficiency.