Texture-based segmentation of satellite weather imagery

被引：7

作者：

Lakshmanan, V ^{[1
]}

DeBrunner, V ^{[1
]}

Rabin, R ^{[1
]}

机构：

[1] Natl Severe Storms Lab, Norman, OK 73069 USA

来源：

2000 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL II, PROCEEDINGS | 2000年

关键词：

D O I：

10.1109/ICIP.2000.899813

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Unsupervised segmentation of weather images into features that correspond to physical storms is a fundamental and difficult problem. Treating an infrared satellite image as a Markov random field, the Kalmogorov-Smirnov distance between the local distribution of spatial statistics and the global statistics of classified regions is used to segment the image using a relaxation algorithm, An outlier class is utilized to capture as yet unclassfied pixels. We demonstrate the results of different initialization methods on the final segmentation and point out where the method is deficient.

引用

页码：732 / 735

页数：2

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