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1)  anomaly pattern
异常图像
1.
By use of many mathematic methods,such as conventional differentiation,analysis of trend rate,the long-medium-short-term anomaly patterns and coseismic step of the tilt observations at Sheshan station before the Sumatra 8.
7级大震前的长中短期异常图像及其同震阶跃。
2)  anomaly image
异常图像
1.
The anomaly images from 5 sets data of crust titles from 1988 to 1998 are analyzed systematically.
系统分析了1988~1998年期间新疆4个台站、5套地倾斜仪记录到的异常图像,发现与周围的4级以上及强远震有较好的对应关系。
2.
though perpendicular pendulum and horizontal pendulum record the same physical quantity,but the difference in anomaly image is very large.
垂直摆倾斜仪与水平摆倾斜仪虽然记录的是同一物理量,但二者的异常图像差别很大。
3)  anomalous image
异常图像
1.
Firstly we conclude the causes of the anomalous images recorded by the digital,fixed deformation station in Lijiang as the following:(1) interference factor,(2) recorded earthquake events,and(3) seismic precursor anomaly.
本文利用丽江地震台数字化定点形变观测记录到的典型异常图像,从干扰因素、同震记录、地震前兆异常三个方面分析总结了典型图像形成的机理。
4)  image anomaly
图像异常
1.
This paper presents several methods for the definition and detection of the image anomaly.
论述了图像异常的定义和检测图像异常的几种方法:滑动窗口法、变换域处理法和图像分类法,以及其在遥感图像中的具体应用。
5)  graphic distinguish
图像异常识别
1.
To solve low efficient and bad stable problem of graphic distinguishment by classical graphic distinguish method,a new method is put forward in this paper,bringing an advanced method of BP neural network into graphic distinguishing area and using this related algorithm to distinguish graphic abnormality after BP neural network training.
将先进的BP神经网络算法理论改进并引入到图像异常识别领域,用经过BP神经网络训练后的相关函数进行图像异常辨识,由于该算法充分考虑了图像像素的位置特征,并能根据图像内容进行自我学习,同传统采用灰度直方图进行辨识的算法相比,具有自适应、鲁棒性强的优点,可获得更高的辨识率。
6)  Anomaly pattern of small earthquakes
弱震异常图像
补充资料:高光谱分辨率遥感图像及图像光谱信息提取


高光谱分辨率遥感图像及图像光谱信息提取


  高光谱分辨率遥感图像及图像光谱信息提取 郑兰芬供稿
  
说明:补充资料仅用于学习参考,请勿用于其它任何用途。
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