期刊文献+
共找到2篇文章
< 1 >
每页显示 20 50 100
应用于工业检测的光照不均匀图像的校正 被引量:6
1
作者 杨欢 《微计算机信息》 2009年第21期244-245,279,共3页
文中提出利用低通滤波的方法实现对光照不均匀图像的校正。该方法的理论依据是在对照明光场的频谱特性进行分析的基础上提出的;接着将滤波器的设计作为重点,针对参数选取问题,提出了以多次滤波逐渐逼近照明光场的方法;最后通过对实验结... 文中提出利用低通滤波的方法实现对光照不均匀图像的校正。该方法的理论依据是在对照明光场的频谱特性进行分析的基础上提出的;接着将滤波器的设计作为重点,针对参数选取问题,提出了以多次滤波逐渐逼近照明光场的方法;最后通过对实验结果的分析,证明该方法能够有效的改善不均匀光照对图像造成的影响。 展开更多
关键词 光照不均匀 低通滤波器 照明光场
下载PDF
Empirical modeling of ionospheric F2 layer critical frequency over Wakkanai under geomagnetic quiet and disturbed conditions 被引量:4
2
作者 LIU Jing LIU LiBo +2 位作者 ZHAO BiQiang WAN WeiXing CHEN YiDing 《Science China(Technological Sciences)》 SCIE EI CAS 2012年第5期1169-1177,共9页
The hourly values of the ionospheric F2 layer critical frequency, foF2, recorded at Wakkanai ionosonde station (45.4°N, 141.7°E) have been collected to construct a middle-latitude single-station model for ... The hourly values of the ionospheric F2 layer critical frequency, foF2, recorded at Wakkanai ionosonde station (45.4°N, 141.7°E) have been collected to construct a middle-latitude single-station model for forecasting foF2 under geomagnetic quiet and disturbed conditions. The module for the geomagnetic quiet conditions incorporates local time, seasonal, and solar vari- ability of climatological foF2 and its upper and lower quartiles. It is the first attempt to predict the upper and lower quartiles of foF2 to account for the notable day-to-day variability in ionospheric foF2. The validation statistically verifies that the model captures the climatological variations of foF2 with higher accuracy than IRI does. The storm-time module is built to capture the geomagnetic storm induced relative deviations of foF2 from the quiet time references. In the geomagnetically disturbed module, the storm-induced deviations are described by diumal and semidiumal waves, which are modulated by a modified magnetic activity index, the Kf index, reflecting the delayed responses of foF2 to geomagnetic activity forcing. The coeffi- cients of the model in each month are determined by fitting the model formula to the observation in a least-squares way. We provide two options for the geomagnetic disturbed module, including or not including Kalman filter algorithm. The Kalman filter algorithm is introduced to optimize these coefficients in real time. Our results demonstrate that the introduction of the Kalman filter algorithm in the storm time module is promising for improving the accuracy of predication. In addition, comparisons indicate that the IRI model prediction of the F2 layer can be improved to provide better performances over this region. 展开更多
关键词 Empirical modeling Kalman f'dter ionospheric storm
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部