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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