基于知识的天气图像处理与分类

遥感信息 Pub Date : 1997-08-03 DOI:10.1109/IGARSS.1997.609156

K.F. Siddiqui

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引用次数: 2

摘要

气象模式和气象资料的卫星图像用于发展基于知识的天气图像处理和分类系统(KB/WIS)。采用小波变换和分形方法对天气图像进行特征提取。提取的特征用于表示各种天气模式。该系统经过统计训练，可以描述和解释天气模式。该系统由图像采集、图像预处理与增强、特征提取与选择、天气推理引擎四个部分组成。介绍了KB/WIS系统的完整体系结构及其应用。

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Knowledge based weather image processing and classification

Satellite imagery of weather patterns and meteorological information are used to develop a knowledge based weather image processing and classification system (KB/WIS). Wavelet and fractal methods are used to extract features from weather images. The features extracted are used to represent various weather patterns. The system is statistically trained to characterize and interpret weather patterns. The system is a composite of four components: image acquisition, image preprocessing and enhancement, feature extraction and selection, and weather inference engine. Complete architecture of the KB/WIS system including its applications is described.

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来源期刊

遥感信息

自引率

0.00%

发文量

3984

期刊介绍： Remote Sensing Information is a bimonthly academic journal supervised by the Ministry of Natural Resources of the People's Republic of China and sponsored by China Academy of Surveying and Mapping Science. Since its inception in 1986, it has been one of the authoritative journals in the field of remote sensing in China.In 2014, it was recognised as one of the first batch of national academic journals, and was awarded the honours of Core Journals of China Science Citation Database, Chinese Core Journals, and Core Journals of Science and Technology of China. The journal won the Excellence Award (First Prize) of the National Excellent Surveying, Mapping and Geographic Information Journal Award in 2011 and 2017 respectively. Remote Sensing Information is dedicated to reporting the cutting-edge theoretical and applied results of remote sensing science and technology, promoting academic exchanges at home and abroad, and promoting the application of remote sensing science and technology and industrial development. The journal adheres to the principles of openness, fairness and professionalism, abides by the anonymous review system of peer experts, and has good social credibility. The main columns include Review, Theoretical Research, Innovative Applications, Special Reports, International News, Famous Experts' Forum, Geographic National Condition Monitoring, etc., covering various fields such as surveying and mapping, forestry, agriculture, geology, meteorology, ocean, environment, national defence and so on. Remote Sensing Information aims to provide a high-level academic exchange platform for experts and scholars in the field of remote sensing at home and abroad, to enhance academic influence, and to play a role in promoting and supporting the protection of natural resources, green technology innovation, and the construction of ecological civilisation.