THE APPLICATION OF ARTIFICIAL NEURAL NETWORK TO CLASSIFICATION PROCESSING OF REMOTE SENSING DIGITAL IMAGES

doi:10.6046/gtzyyg.1998.01.04

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Abstract

In recent years, with the development of the theory about Artificial Neural Network(ANN) system, the neural network technology is becoming increasingly an effective means of classification processing of remote senser digital images and beginning to replace the Maximum Likelihood Classifier(MLC). This paper discusses some ANN methods that have been very effectively applied abroad. these methods have vast prospects on digital image processing. At last, some principled problems about the practical application of the methods to remote sensing data classification are discussed.

Keywords Pseudo cross variogram Multitemporal texture Change detection

Issue Date: 02 August 2011

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	LI Shu-Kun
	LI Pei-Jun
	CHENG Tao
	TANG Jie
	LEI Jian-Wei
	LIU Yong

Cite this article:

LI Shu-Kun,LI Pei-Jun,CHENG Tao, et al. THE APPLICATION OF ARTIFICIAL NEURAL NETWORK TO CLASSIFICATION PROCESSING OF REMOTE SENSING DIGITAL IMAGES[J]. REMOTE SENSING FOR LAND & RESOURCES, 1998, 10(1): 21-27.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.1998.01.04 OR https://www.gtzyyg.com/EN/Y1998/V10/I1/21

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