SELF-ADAPTIVE SEGMENTATION FOR INFRARED SATERLLITE CLOUD IMAGE

机译：红外卫星云图像的自适应分割

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It is difficult to segment cloud images because of the complicated and various shapes and blurry edges of cloud. In this paper, we present an idea and a set of realizable design about self-adaptive segmentation by means of mathematical morphology. Created models can show some characteristics of clouds such as shapes, scales and temperature exactly. Some practices show that the segmentation models are self-adaptive, the program is general and the algorithm is high efficient with the parallel operation.

机译：由于云的形状复杂而多样，边缘模糊，因此很难分割云图像。在本文中，我们提出了一种基于数学形态学的自适应分割的思路和一套可实现的设计。创建的模型可以准确显示云的某些特征，例如形状，比例和温度。一些实践表明，分割模型是自适应的，程序通用，算法具有并行操作的高效性。

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来源
《Conference on Image Extraction, Segmentation, and Recognition Oct 22-24, 2001, Wuhan, China》|2001年|p.388-393|共6页
会议地点 Wuhan(CN)
作者
Wang Ping; Xue Juntao; Liu Zhengguang; Liu Huanzhu; Tang Guisheng;
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作者单位

School of Electronic Engineering and Energy, Tianjin University, China 300072;

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会议组织
原文格式 PDF
正文语种 eng
中图分类无线电电子学、电信技术;
关键词
self-adaptive segmentation; infrared satellite cloud image; mathematical morphology;

机译：自适应分割红外卫星云图；数学形态学;

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4. SELF-ADAPTIVE SEGMENTATION FOR INFRARED SATERLLITE CLOUD IMAGE [C] . Xu, Tang Guisheng, Liu Huanzhu, Conference on image extracting, segmentation, and recognition . 2001

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SELF-ADAPTIVE SEGMENTATION FOR INFRARED SATERLLITE CLOUD IMAGE

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