Application of Decision Tree on Multispectral Images Based on Segment and Scale-Span Features

Existing classification methods,based on the homogeneous-region,mostly involve the best segmentation criterion choice.Using the so-called best-scale to classify the multi-scale objects defined by human subjectivity,the paper doesn't think it is the best way for classification.So the paper proposes a new multi-scale homogeneous-region model,fully using the longitudinal information which the homogeneous-region model provides,and adopting the scale-span classification method based on decision tree to improve the accuracy,without selecting the best-scale data.The result shows this method can distinguish objects accurately and improve the precision than sole scale classification.