遥感图像分类自动选取最优波段组合的方法研究

在遥感影像计算机自动识别与分类中,选取最佳的波段子集对地物进行分类对提高分类精度至关重要。根据统计学原理,遥感影像中属于某类别地物的特征向量服从正态分布,训练样本的正态性检验是关键,基于此理论,本文利用TM影像数据,通过检验所选取的训练区的正态性与否,让计算机自动的选取最优的波段组合,并对分类的精度进行评估。研究表明,计算机自动选取最佳波段组合后对分类精度的预先评估,较常规分类后再进行数据检验精度评估方法方便,快捷,省时,省力。

Approach study of remote sensing image classification by automatically extracting the optimal bands

In remote sensing image automatic identification and classification of the computer,selecting the best band subset is es- sential to improve classification accuracy.According to statistical theory,in remote sensing images,the eigenvectors of surface features belong to a certain type are subjected to normal distribution.So the normal test to training samples is the key;based on this theory, this paper using TM image data,through the examination of the training area is Normal or not,let the computer automatically select the best combination of bands,and to assess the accuracy of classification.Research shows that the pre-assessment to the classification ac- curacy after the computer automatically selecting the best combination of bands,are more convenient,faster,time-saving and effort than the conventional the accuracy test data.