摘要
在高分辨率遥感图像中,可以在没有任何先验知识的前提下,仅采用待处理图像本身的色调特征,基于植被视觉认知特征,高精度地提取出植被区域。为了提高该方法在色调较暗图像中的提取精度,在简要阐述该方法原理的基础上,针对该方法在色调较暗图像中容易发生非植被区域误判、植被信息提取精度不高的不足,对其进行了技术改进——将植被指数(NDVI)法加入到该方法中,并在检测植被区域轮廓前进行一次数学形态学闭运算。改进后的方法可以很好地去除非植被区域的误判,使其在色调偏暗的图像中也具有一定的提取精度,扩展了该方法的适用范围。
According to the visual characteristics of vegetation, the vegetation areas in the high resolution remote sensing images can be extracted accurately without any transcendental knowledge by using the tonal characteristics of the image itself. Following a brief introduction to the principle of the method, the authors add the NDVI vegetation index to the method which could previously only be applied to the bright tonal, thus overcoming the shortcomings of misjudgments of non - vegetation areas and poor accuracy of vegetation extraction. Morphological closing operation is conducted before the detection of the vegetation region contour. The improved method can resolve the misjudgments of non -vegetation areas significantly, qualifying it for a certain extraction accuracy even in the image whose tonal is somewhat dark, thus expanding the application of the method.
出处
《国土资源遥感》
CSCD
北大核心
2013年第2期75-80,共6页
Remote Sensing for Land & Resources
基金
华南理工大学亚热带建筑科学国家重点实验室开放研究项目(编号:2011KB11)
国家自然科学基金项目(编号:40701103)共同资助
关键词
植被视觉特征
植被指数(NDVI)
闭运算
vegetation visual characteristics
normalized difference vegetation index（NDVI）
closing operation
