The application of probability neural network in remote sensing image processing based on k-means

被引：0

作者：

Hu, Min ^{[1
]}

Li, Feng-Jun ^{[1
]}

机构：

[1] Ningxia Univ, Sch Math & Stat, Yinchuan, Peoples R China

来源：

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMMUNICATION AND ELECTRONIC INFORMATION ENGINEERING (CEIE 2016) | 2016年 / 116卷

基金：

中国国家自然科学基金;

关键词：

Image Classification; Kaufman Approach; K-Means Clustering; Probability Neural Network; MEANS CLUSTERING-ALGORITHM; CLASSIFICATION;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, we design an approach which is a combination of k-means clustering and probability neural network method to classify the remote sensing image. The proposed method allows the implementation of Kaufman approach to get clustering centers, which are used as initial centers in k-means algorithm. Then the image is divided into k number of clusters by using the k-means algorithm. Finally, the pixels are divided into k classes according to probability neural network. The results indicate that the classified image is consistent with the original image and all kinds of characteristics are relatively well preserved.

引用

页码：724 / 730

页数：7

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