Improvement of the automatic recognition method based on vegetation visual characteristics
LI Cheng1,2, CHEN Renxi1,2, WANG Qiuyan1
1. School of Earth Sciences and Engineering, Hohai University, Nanjing 210098, China; 2. State Key Laboratory of Subtropical Building Science of South China University of Technology, Guangzhou 510640, China
Abstract：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.
李成, 陈仁喜, 王秋燕. 改进的基于视觉认知特征的植被识别方法[J]. 国土资源遥感, 2013, 25(2): 75-80.
LI Cheng, CHEN Renxi, WANG Qiuyan. Improvement of the automatic recognition method based on vegetation visual characteristics. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(2): 75-80.
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2013, Vol. 25 
