摘要
针对噪声导致高分辨遥感影像分割存在过分割或者欠分割的问题,提出结合相位一致和分水岭变换的高分辨率影像分割方法。该方法首先采用基于光谱相似性的相位一致的模型方法来获得边缘响应幅度,再采用自动标记分水岭算法对影像进行分割;基于相邻分割对象的空间位置、形状、面积等特征多重约束,提出相邻分割对象合并代价函数模型,对分割结果进行优化并获取最终分割结果。选择典型地区实验影像进行分割实验,通过目视评价和监督评价,并与典型分割方法进行比较,验证所提分割方法的有效性。
In consideration of the problem of over-segmentation or under-segmentation in high-resolution remote sensing image segmentation that the noise leads to,a high-resolution image segmentation method with phase consistency and watershed transformation is proposed.Firstly,the phase-consistent model method with spectral similarity is adopted to obtain the edge response amplitude,and then the automatic marker watershed algorithm is adopted to segment the image.Based on the multiple restrictions for the features,such as spatial position,shape and area of adjacent segmentation objects,adjacent segmentation object merging cost function model is proposed to optimize the segmentation result and obtain the final segmentation result.Experimental images of the typical area are selected for the segmentation experiment.The effectiveness of the proposed method is verified by visual evaluation,supervision evaluation and comparison with the typical segmentation methods.
出处
《激光与光电子学进展》
CSCD
北大核心
2017年第9期375-380,共6页
Laser & Optoelectronics Progress
基金
国家自然科学基金(41101452)
高等学校博士学科点专项科研基金(20112121120003)
辽宁省教育厅科研项目(LJYL010)
关键词
遥感
高分辨率遥感影像
相位一致性
分水岭变换
影像分割
remote sensing
high resolution remote sensing image
phase consistency
watershed transformation
image segmentation
