Classification optimization is a practical subject which deserves exploration. In order to study mode filter and its application to the post-processing of remote sensing classification, the authors, on the basis of detailed analysis of the principle of the nonlinear mode filter and in view of the characteristics of 2D and 3D data, developed various aspects of the filter to make it suitable for the classification of remote sensing data. Taking remote sensing image and airborne LiDAR point clouds as examples, the authors discussed the developed scheme from two respects and four respects, and the nearest neighbor Mode filter and window-based Mode filter were used to improve the classification results of the two types of data, respectively. Contrastive experimental results demonstrate that the developed Mode filters can remove the speckle and salt and pepper noises effectively, reduce greatly the misclassification points derived from point clouds and remote sensing image, and boost the Kappa value and overall accuracy after classification of the two data remarkably, thus achieving the desired goal.
董保根, 车森, 解龙根, 单国慧, 何乔. Mode滤波器及其在遥感分类后处理中的应用[J]. 国土资源遥感, 2016, 28(2): 62-66.
DONG Baogen, CHE Sen, XIE Longgen, SHAN Guohui, HE Qiao. Mode filter and its application to post-processing of remote sensing classification. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(2): 62-66.
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2016, Vol. 28 
