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   optimal band combinations 在 自然地理学和测绘学 分类中 的翻译结果: 查询用时:0.513秒
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optimal band combinations
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As a case study of merging QuickBird multispectral and panchromatic remote sensing image, Brovey,IHS,PCA and Synthetic Variable Ratio(SVR) are choosen and their merging effects are evaluated quantificationally by difference index and average gradient; bands of merged image choosen to produce basic map are determined by optimium index factor(OIF). It is indicated that merging effect of SVR is beyond orther 3 algorithms;the optimal band combination is 431 which is applied to establish identification...

As a case study of merging QuickBird multispectral and panchromatic remote sensing image, Brovey,IHS,PCA and Synthetic Variable Ratio(SVR) are choosen and their merging effects are evaluated quantificationally by difference index and average gradient; bands of merged image choosen to produce basic map are determined by optimium index factor(OIF). It is indicated that merging effect of SVR is beyond orther 3 algorithms;the optimal band combination is 431 which is applied to establish identification and analyse criterion of substances on earth surface for visual interpretation;tolerance-grid-digitalization method is used for screen-digitization in producing basic map for agricultural zone.

应用比值变换、IHS变换、主成分变换和合成比值变量变换等4种影像融合方法对QuickBird多光谱和全色遥感影像进行融合,并利用偏差指数、平均梯度等指标对融合效果进行定量评价;运用最佳指数因子确定参与成图的多光谱影像的波段.研究结果表明,合成比值变量变换法的融合效果最佳;最优波段组合为431,并在此基础上建立了地物判读分析依据,用于QuickBird遥感影像目视解译;采用容差格网矢量化技术进行遥感影像的屏幕矢量化,制作了1:2000比例尺农业园区底图.

The optimal band combinations were selected for interpretation of land use/cover..Based on this,the multilayer extrastion was presented.Land use/cover information is interpreted by using the method,at the same time the interpretation results are evaluated.The results show that TM3,4,5 is the optimal combination for classifying cultivated,forest and grassland,and that TM1,4,5 is the optimal combination for classifying residential area and water body.Compared with the unsupervised...

The optimal band combinations were selected for interpretation of land use/cover..Based on this,the multilayer extrastion was presented.Land use/cover information is interpreted by using the method,at the same time the interpretation results are evaluated.The results show that TM3,4,5 is the optimal combination for classifying cultivated,forest and grassland,and that TM1,4,5 is the optimal combination for classifying residential area and water body.Compared with the unsupervised classification and the supervised classification,the precision of multiband combination information extraction is improved to 85.5% from 25.3%,71.6%,respectively.

针对不同土地利用类型,选取最佳解译波段组合。在此基础上,提出分层提取的方法,并用此法对土地利用/覆盖信息进行了解译,同时进行了精度评价。结果表明:TM1,4,5组合为解译居民点和水域的最佳波段组合,TM3,4,5组合为解译耕地、林地和草地的最佳波段组合;与非监督分类及监督分类相比,监督分类和非监督分类结合分层提取的总体分类精度分别从25.3%、71.6%提高到85.5%。

In this paper,a case study on the feature selection and extraction of the hyperspectral data of HyMap(128 bands) in Barrax,Spanish,is carried out based on K-L transform,segment K-L transform,wavelet transform,band index and some separability functions so as to select the optimal band combinations of the spectra of land covers.The original HyMap data were derived from Barrax test site in Spanish at 9:00 o’clock,June 4,1999,the air altitude was 3 500 m,and the spatial resolving power was about 5 m.the spectral...

In this paper,a case study on the feature selection and extraction of the hyperspectral data of HyMap(128 bands) in Barrax,Spanish,is carried out based on K-L transform,segment K-L transform,wavelet transform,band index and some separability functions so as to select the optimal band combinations of the spectra of land covers.The original HyMap data were derived from Barrax test site in Spanish at 9:00 o’clock,June 4,1999,the air altitude was 3 500 m,and the spatial resolving power was about 5 m.the spectral range of HyMap airborne imaging spectrometer was 400~2 480 nm,there were 128 wavebands except two with high vapor absorption near 1.4 μm and 1.9 μm.The wavebands can be divided into 4 groups,i.e.,the visible light,near infrared rays,shortwave infrared ray 1 and shortwave infrared ray 2,each waveband group includes 32 wavebands,and the waveband width is about 16 nm.The atmospheric correction and geometry correction of the test data are carried out,and the values of reflectivity of the ground objects are normalized.The classification accuracies of different methods of the feature selection and extraction are compared and analyzed based on the common supervised classification methods,such as the maximum likelihood,parallelepiped and minimum distance.The results show that the classification accuracy with feature selection based on band indexes and average dispersibility is high,and that with feature extraction based on K-L transform,segment K-L transform and wavelet transform is high.The compared and analyzed results show that the classification accuracy of the parallelepiped is relatively low,that of minimum distance is relatively high,and that of the maximum likelihood stable.

以西班牙Barrax地区的HyMap数据为例,利用K-L变换、波段指数、分段K-L变换、小波变换和可分性准则等常见的特征选择和提取方法,进行了特征提取和特征选择;然后,基于常用的监督分类法,通过各自的分类精度对各特征提取和特征选择法进行了比较和分析。实验结果表明使用可分性准则进行的特征选择时,基于波段指数、离散度平均值的分类精度相对较高;基于变换的特征选择中,K-L变换、分段K-L变换和小波变换的分类精度较高,三者基本上一致。而在监督分类方法的比较分析上,平行六面体法相对较差,最小距离法分类精度则相对较高,而最大似然法则比较稳定。

 
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