BANDC——一种适合于从遥感图象识别地理环境的分类器

BANDC—A CLASSIFIER FOR GEOGRAPHICAL ENVIRONMENTS RECOGNITION FROM REMOTE SENSING IMAGES

  • 摘要: 本文所提出的新算法BANDC是Bayes Normal Dynamic Clustering的缩写.这个算法的目的是从遥感图象识别地理环境.它的优点是:能由机器自动按照图象估算出分类器的参数;作为一种特殊的Bayes分类器,它能够依靠计算机估算出wi的先验概率,于是能剔除野点,提高分类器的鲁棒性.这个算法的关键是应用拟合法从灰度等级直方图估算出参数.

     

    Abstract: A new classifying algorithms,BAyes Normal Dynamic Clustering,abbreviated as BANDC,is presented in this paper,chiefly for geographical environments recognition from remot sensing images.It has two advantages:1)the ability to estimate the parameters of the classifier from the images by self-discipline;2)as a special Bayes classifier,it can estimate prior probabilities of W_i by the computer and pick out ill-point,thus increasing the robustness of the classifier.The knack of this algorithms is the estimation of the parameters from the grey level histogram by using fitting techniques.It involved the Bayes rule criterion function and the estimation of the peak positions of the histogram.

     

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