面向对象的山地区域多源遥感影像分割尺度选择及评价

Evaluation and Selection of Segmentation Scale with Object-oriented Method in Multiple Source Remote Sensing Image of Mountain Areas

随着遥感技术的飞速发展,通过各种传感器获取的影像种类越来越多。传统的面向像元的影像分析技术已难以适应高分辨率影像,面向对象的影像分析技术应运而生。面向对象的影像分析技术所面临的首要问题是影像分割,如何选择合适的影像分割尺度已成为面向对象影像分析技术的关键。为了提高遥感影像分割尺度选择的准确性,通过对影像分析建立了分割质量函数,针对不同分辨率的多源遥感影像进行分割实验,获取了最优分割尺度,最后提出了一种顾及面积和光谱的分割匹配指数对最优分割尺度进行评价,并研究了分割尺度与亮度均值标准差、影像空间分辨率之间的对应关系。研究结果表明,构建的分割质量函数获取的最优分割尺度避免了人工分割带来的主观性,建立的同时顾及面积和光谱因子的分割匹配指数验证了最优分割尺度选择的正确性。

With the rapid development of remote sensing technology,more and more kinds of images were obtained through all sorts of sensor.Traditional pixel-based image analysis technique has been difficult to adapt to the high resolution images,and the object-oriented image analysis technique came into being.The image segmentation is the top issue of the object-oriented image analysis technique,how to choose the right image segmentation scale has become the key of object-oriented analysis technology.In order to improve the accuracy of remote sensing image segmentation scale,a segmentation quality function was established through analysis of images.Segmentation experiments according to different resolution multi-source remote sensing images,and the optimal segmentation scale was obtained.Finally a segmentation matching index which considering area and spectrum was proposed to evaluate the optimal segmentation scale,and the relationship between segmentation scale and standard deviation of the mean brightness,image spatial resolution were discussed.Experimental results show that the optimal segmentation scale was obtained by this segmentation quality function can avoid the subjectivity brought on manual segmentation.And the proposed segmentation matching index which considering area and spectrum was validated the correctness of the optimal segmentation scale selection.