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31.
With increasing interest in displacement spectra and long‐period motions, it is important to check the sensitivity of both elastic and inelastic response spectra to the filtering that is often necessary to remove long period artifacts, even from many modern digital recordings. Using two records of very different character from the M=7.1, 1999 Hector Mine, California, earthquake, we find that the response spectra can be sensitive to the corner periods used in causal filtering, even for oscillator periods much less than the filter corner periods. The effect is most pronounced for inelastic response spectra, where the ratio of response spectra computed from accelerations filtered at 25 and 200 sec can be close to a factor of 2 for oscillator periods less than 5 sec. Published in 2003 by John Wiley Sons, Ltd. 相似文献
32.
由于光照的变化和全景视觉的畸变,全自主足球机器人对目标识别不稳定且有效性差,为此提出了1种基于Gabor滤波器和支持向量机(SVM)的全自主足球机器人目标识别方法。首先根据颜色特征和面积、长宽比等简单形状特征提取候选目标,候选目标中包含实际的目标和与目标颜色相近且通过上述简单形状特征判断仍无法消除的干扰。将候选目标与Gabor滤波器作卷积来提取特征向量,将特征向量输入SVM进行分类,识别出实际的目标。在机器人MT-R的足球目标识别中对该方法进行了实验,实验表明该种方法具有较好的识别精度,且满足足球机器人的实时性要求。 相似文献
33.
This contribution discusses the application of Chebyshev Type I filter for processing real earthquake records. Consideration
is given to the effects of filtering parameters (passband amplitude ripple and order of the filter) on the time series, strong-motion
parameters, Fourier Amplitude Spectrum of acceleration, and elastic displacement response spectra. Time histories of five
earthquakes with different moment magnitudes have been examined (from stations located close to the epicenters). Data processing
is based on application of bandpass Chebyshev filtering over frequency range with substantial signal to noise ratio (level
of 3 or approximately 3 dB). Applying different filters, we have monitored several important strong-motion parameters: peak
values of acceleration, velocity, and displacement; Arias intensity, acceleration/velocity spectrum intensity, significant
duration, etc. Some new results and conclusions concerning the influence of Chebyshev filter in data processing of records
have been summarized. The graphical and numerical outcomes obtained, as well as the comparison with a Butterworth causal filter,
are included in the work. The results could be potentially useful to engineering seismologists who need to evaluate and better
understand the merits of this type of filtering for strong-motion data processing. 相似文献
34.
针对不同时期高分辨率遥感影像变化检测中城区建筑物因投影差差异所产生的误检测现象,提出了一种综合应用光谱和纹理特征的建筑物变化检测方法。以变化和未发生变化地物影像的散度作为可分性依据,首先对光谱差分影像在混合高斯密度模型下建模,并采用马尔可夫最小错误概率准则提取初始变化区域,往往含有错判的建筑物。然后将误判建筑物影像类和真实变化影像类构成训练集,通过引入多通道Gabor滤波器,提取训练集的纹理差分特征,并采用分类别PCA变换实施纹理差分特征的选择。最后对选择出的纹理差分特征依据高斯混合密度模型建模,并用马尔可夫最小错误概率提取真变化区域,即可去除光谱信息检测所产生的伪变化。试验表明,本文方法能够较好地解决建筑物变化的错判问题,提高了影像变化检测的精度。 相似文献
35.
贺兰山地区大气冰核浓度的测量及初步分析 总被引：10，自引：2，他引：8
根据 1 994年在银川和阿拉善左旗观测得到的冰核资料 ,给出了两地不同天气条件下的大气冰核浓度 ,分析并讨论了冰核浓度与风、降水、天空状况等的关系 ,给出了飞机在空中测量冰核的结果。 相似文献
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39.
《International Journal of Digital Earth》2013,6(2):186-193
Abstract According to the features of high-resolution panchromatic imagery of Beijing-1 small satellite, an approach to extracting information of residential areas is proposed in this paper based on Gabor texture segmentation. The algorithm extracts the features in different directions and different scales by building the Gabor filter, uses cluster analysis of multiple features to segment the image, and performs the fusion processing based on morphological scale space. It solves the problems in image processing resulting from low contrast between remote sensing objects and background, the blurring of image edges and high noise. It has the benefits of direction selection and frequency selection with strong self-adaptive ability. Our experiments prove the effectiveness of the approach for extracting information of residential areas from Beijing-1 high-resolution imagery. 相似文献
40.
《International Journal of Digital Earth》2013,6(5):351-372
This study compares the spectral sensitivity of remotely sensed satellite images, used for the detection of archaeological remains. This comparison was based on the relative spectral response (RSR) Filters of each sensor. Spectral signatures profiles were obtained using the GER-1500 field spectroradiometer under clear sky conditions for eight different targets. These field spectral signature curves were simulated to ALOS, ASTER, IKONOS, Landsat 7-ETM+, Landsat 4-TM, Landsat 5-TM and SPOT 5. Red and near infrared (NIR) bandwidth reflectance were re-calculated to each one of these sensors using appropriate RSR Filters. Moreover, the normalised difference vegetation index (NDVI) and simple ratio (SR) vegetation profiles were analysed in order to evaluate their sensitivity to sensors spectral filters. The results have shown that IKONOS RSR filters can better distinguish buried archaeological remains as a result of difference in healthy and stress vegetation (approximately 1–8% difference in reflectance of the red and NIR band and nearly 0.07 to the NDVI profile). In comparison, all the other sensors showed similar results and sensitivities. This difference of IKONOS sensor might be a result of its spectral characteristics (bandwidths and RSR filters) since they are different from the rest of sensors compared in this study. 相似文献