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Adaptive majority filtering for contextual classification of remote sensing data

 

作者: KWANGE. KIM,  

 

期刊: International Journal of Remote Sensing  (Taylor Available online 1996)
卷期: Volume 17, issue 5  

页码: 1083-1087

 

ISSN:0143-1161

 

年代: 1996

 

DOI:10.1080/01431169608949070

 

出版商: Taylor & Francis Group

 

数据来源: Taylor

 

摘要:

This Letter presents an adapiive contexiual filler, developed by Ihe addition of a heterogeneity rule and a confidence rule to The conventional majority filter. Experiments have been carried out using a Landsat Thematic Mapper (TM) image. Results show that the adaptive majority filter has a capability of reducing the classification errors due to spectrally mixed pixels and preserves The connection of thin features. The proposed filler needs only a moderate increase in processing time compared with the conventional majority filter.

 

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