Pub Date : 2013-01-01DOI: 10.3724/sp.j.1010.2013.00450
Che Hong
Two nonlinear dimensionality reduction methods were proposed based on image Euclidean distance. Considering the physical characters of hyperspectral imagery,the methods introduced image Euclidean distance into traditional manifold dimensionality reduction. Compared w ith other methods,our methods have several advantages. The introduction of image Euclidean distance not only considers hyperspectral image's spatial relationship,but also preserves the local feature of datasets w ell. Thus the proposed methods can discard efficiently the redundant information from both the spectral and spatial dimensions. The experiment results demonstrated that the proposed methods have higher classification accuracy than other methods w hen applied to hyperspectral image classification.
{"title":"Image Euclidean distance-based manifold dimensionality reduction algorithm for hyperspectral imagery","authors":"Che Hong","doi":"10.3724/sp.j.1010.2013.00450","DOIUrl":"https://doi.org/10.3724/sp.j.1010.2013.00450","url":null,"abstract":"Two nonlinear dimensionality reduction methods were proposed based on image Euclidean distance. Considering the physical characters of hyperspectral imagery,the methods introduced image Euclidean distance into traditional manifold dimensionality reduction. Compared w ith other methods,our methods have several advantages. The introduction of image Euclidean distance not only considers hyperspectral image's spatial relationship,but also preserves the local feature of datasets w ell. Thus the proposed methods can discard efficiently the redundant information from both the spectral and spatial dimensions. The experiment results demonstrated that the proposed methods have higher classification accuracy than other methods w hen applied to hyperspectral image classification.","PeriodicalId":50181,"journal":{"name":"红外与毫米波学报","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69889458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-01-01DOI: 10.3724/sp.j.1010.2013.00414
H. Zhang
Based on the coupling wave theory and phase re-matching technique,a Q-band TE01-TE11circular w aveguide mode converter for transmitting high pow er microw ave has been designed and analyzed by numerical calculation and simulation. Results of 4-period and 6-period mode converter are demonstrated in this paper. The numerical calculation show that maximum conversion efficiency is 98. 82% and bandw idth is over 2. 2GHz for 4-period structure. How ever,for the6-period one,the maximum conversion efficiency is 99. 89% and bandw idth is over 1. 7GHz. It also presented the influence of the key parameters on the conversion efficiency. Simulated results from HFSS agreed w ell w ith the numerical calculation. Based on the theory and simulated results,a mode converter w as fabricated and tested. It turned out that a pure TE11mode w as abtained.
{"title":"Q-band TE_(01)-TE_(11) high power microwave mode converter","authors":"H. Zhang","doi":"10.3724/sp.j.1010.2013.00414","DOIUrl":"https://doi.org/10.3724/sp.j.1010.2013.00414","url":null,"abstract":"Based on the coupling wave theory and phase re-matching technique,a Q-band TE01-TE11circular w aveguide mode converter for transmitting high pow er microw ave has been designed and analyzed by numerical calculation and simulation. Results of 4-period and 6-period mode converter are demonstrated in this paper. The numerical calculation show that maximum conversion efficiency is 98. 82% and bandw idth is over 2. 2GHz for 4-period structure. How ever,for the6-period one,the maximum conversion efficiency is 99. 89% and bandw idth is over 1. 7GHz. It also presented the influence of the key parameters on the conversion efficiency. Simulated results from HFSS agreed w ell w ith the numerical calculation. Based on the theory and simulated results,a mode converter w as fabricated and tested. It turned out that a pure TE11mode w as abtained.","PeriodicalId":50181,"journal":{"name":"红外与毫米波学报","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69889805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-01-01DOI: 10.3724/sp.j.1010.2013.00062
Z. Chun
Hyperspectral image classification is an important research aspect of hyperspectral data analysis.Relevance vector machine(RVM) is widely utilized since it is not restricted to Mercer condition and does not have to set the penalty factor.Due to the high dimension of hyperspectral data,the classification accuracy is severely affected when there are few training samples.Feature reduction is a common method to deal with this phenomenon.However,most of the filter model based feature selection methods can not provide optimal feature selection number.This paper proposes to utilize the statistic estimation characteristic of Monte Carlo random experiments to calculate optimal feature reduction number and conduct hyperspectral image classification with relevance vector machine.Experimental results show the reliability of the feature reduction number calculated by Monte Carlo method.Compared with the classification of original data,there is a significant improvement in the classification accuracy with the feature reduction data.
{"title":"Hyperspectral image classification based on Monte Carlo feature reduction method","authors":"Z. Chun","doi":"10.3724/sp.j.1010.2013.00062","DOIUrl":"https://doi.org/10.3724/sp.j.1010.2013.00062","url":null,"abstract":"Hyperspectral image classification is an important research aspect of hyperspectral data analysis.Relevance vector machine(RVM) is widely utilized since it is not restricted to Mercer condition and does not have to set the penalty factor.Due to the high dimension of hyperspectral data,the classification accuracy is severely affected when there are few training samples.Feature reduction is a common method to deal with this phenomenon.However,most of the filter model based feature selection methods can not provide optimal feature selection number.This paper proposes to utilize the statistic estimation characteristic of Monte Carlo random experiments to calculate optimal feature reduction number and conduct hyperspectral image classification with relevance vector machine.Experimental results show the reliability of the feature reduction number calculated by Monte Carlo method.Compared with the classification of original data,there is a significant improvement in the classification accuracy with the feature reduction data.","PeriodicalId":50181,"journal":{"name":"红外与毫米波学报","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69888381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-01-01DOI: 10.3724/sp.j.1010.2013.00389
Zhao Shou
A revised method to evaluate parameters of solar cell from current-voltage characteristics,under illuminated or non-illuminated conditions,w as described. The series resistance( R s),the shunt resistance( R sh),the ideality factor( n),and the reverse saturation current density( J0) were extracted using the two diode circuit model from selected regions of the J-V curves. Using the presented model,more parameters w ith higher fitted precision have been extracted from experimental J-V curves of a CdS / CdTe thin film solar cell than using a single diode circuit one.
{"title":"Numerical analysis of the non-ideal current-voltage characteristics of solar cell","authors":"Zhao Shou","doi":"10.3724/sp.j.1010.2013.00389","DOIUrl":"https://doi.org/10.3724/sp.j.1010.2013.00389","url":null,"abstract":"A revised method to evaluate parameters of solar cell from current-voltage characteristics,under illuminated or non-illuminated conditions,w as described. The series resistance( R s),the shunt resistance( R sh),the ideality factor( n),and the reverse saturation current density( J0) were extracted using the two diode circuit model from selected regions of the J-V curves. Using the presented model,more parameters w ith higher fitted precision have been extracted from experimental J-V curves of a CdS / CdTe thin film solar cell than using a single diode circuit one.","PeriodicalId":50181,"journal":{"name":"红外与毫米波学报","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69889129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-01-01DOI: 10.3724/sp.j.1010.2013.00298
Z. Chuan
CdS thin films were deposited on the substrate at temperature of 300 ℃ by magnetron sputtering. The deposited films were annealed at temperature of 370℃,380 ℃ and 390 ℃,respectively,in either atmosphere of dry air or a mixture of CdCl2and dry air. The morphology,structure and optical properties before and after thermal annealing were investigated. The results show that for samples annealed in dry air,the variations of grain size,surface roughness and visible light transmittance with annealing temperature are not obvious,while the optical band gap increases with temperature increasing. Annealed in the mixture of CdCl2and dry air,recrystallization and grain growth in the samples are significant. Surface roughness increases with temperature increasing,on the contrary,visible light transmittance and optical band gap decreases. These phenomena are the results of changes in the temperature of recrystallization and doping concentration in the band tail states at different annealing atmosphere.
{"title":"Effect of different annealing conditions on the properties of CdS thin films deposited by magnetron sputtering","authors":"Z. Chuan","doi":"10.3724/sp.j.1010.2013.00298","DOIUrl":"https://doi.org/10.3724/sp.j.1010.2013.00298","url":null,"abstract":"CdS thin films were deposited on the substrate at temperature of 300 ℃ by magnetron sputtering. The deposited films were annealed at temperature of 370℃,380 ℃ and 390 ℃,respectively,in either atmosphere of dry air or a mixture of CdCl2and dry air. The morphology,structure and optical properties before and after thermal annealing were investigated. The results show that for samples annealed in dry air,the variations of grain size,surface roughness and visible light transmittance with annealing temperature are not obvious,while the optical band gap increases with temperature increasing. Annealed in the mixture of CdCl2and dry air,recrystallization and grain growth in the samples are significant. Surface roughness increases with temperature increasing,on the contrary,visible light transmittance and optical band gap decreases. These phenomena are the results of changes in the temperature of recrystallization and doping concentration in the band tail states at different annealing atmosphere.","PeriodicalId":50181,"journal":{"name":"红外与毫米波学报","volume":"162 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69889260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-01-01DOI: 10.3724/sp.j.1010.2013.00538
Luan Hai
The continuous spatial scaling model(CSSM) of NDVI based on fractal theory was proposed and implemented.Based on GEOEYE-1 image and taking NDVI as experimental object,the paper studied the availability of fractal methodology for high-resolution image,and discussed the selection of the best reasonable scale-level for establishing NDVI's CSSM.It w as concluded that the fractal methodology is suitable for high-resolution RS image.In some definite conditions,the best reasonable scale-level for establishing NDVI's CSSM exists and can be computed.For the fractal methodology,the results in the paper extended its available range of retrievals and image's resolutions.
{"title":"Establishing continuous scaling of NDVI based on fractal theory and GEOEYE-1 image","authors":"Luan Hai","doi":"10.3724/sp.j.1010.2013.00538","DOIUrl":"https://doi.org/10.3724/sp.j.1010.2013.00538","url":null,"abstract":"The continuous spatial scaling model(CSSM) of NDVI based on fractal theory was proposed and implemented.Based on GEOEYE-1 image and taking NDVI as experimental object,the paper studied the availability of fractal methodology for high-resolution image,and discussed the selection of the best reasonable scale-level for establishing NDVI's CSSM.It w as concluded that the fractal methodology is suitable for high-resolution RS image.In some definite conditions,the best reasonable scale-level for establishing NDVI's CSSM exists and can be computed.For the fractal methodology,the results in the paper extended its available range of retrievals and image's resolutions.","PeriodicalId":50181,"journal":{"name":"红外与毫米波学报","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69889576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-01-01DOI: 10.3724/sp.j.1010.2013.00231
Zhang Xiang
As a nonlinear dimension reduction algorithm,Gaussian process latent variable model(GPLVM) has been widely applied in pattern recognition and computer vision for its capability in dealing with small size and high-dimensional samples.As GPLVM can discover low-dimensional manifolds in high-dimensional data given only a small number of samples,a new SAR target recognition method was proposed,in which a modified GPLVM was used for feature extraction and Gaussian process classification was employed as the classifier.In GPLVM,the likelihood was optimized by using the scaled conjugate gradient.In order to avoid the noise effect to gradient estimate and overcome the disadvantage that the performance is severely affected by the step length,the immune clone selection algorithm based GPLVM was developed for target feature extraction where the immune clonal selection algorithm characterized by rapid convergence to global optimum was utilized to improve the performance.The experimental results show that the method not only reduces the dimension but also gets higher accuracy.
高斯过程潜变量模型(Gaussian process latent variable model, GPLVM)作为一种非线性降维算法，以其处理小尺寸高维样本的能力在模式识别和计算机视觉中得到了广泛的应用。针对GPLVM可以在少量样本情况下从高维数据中发现低维流形的特点，提出了一种新的SAR目标识别方法，该方法利用改进的GPLVM进行特征提取，采用高斯过程分类作为分类器。在GPLVM中，使用缩放共轭梯度对似然进行优化。为了避免噪声对梯度估计的影响，克服步长对梯度估计性能影响较大的缺点，提出了基于GPLVM的免疫克隆选择算法进行目标特征提取，利用快速收敛到全局最优的免疫克隆选择算法提高目标特征提取的性能。实验结果表明，该方法不仅降低了尺寸，而且获得了较高的精度。
{"title":"Gaussian process latent variable model based on immune clonal selection for SAR target feature extraction and recognition","authors":"Zhang Xiang","doi":"10.3724/sp.j.1010.2013.00231","DOIUrl":"https://doi.org/10.3724/sp.j.1010.2013.00231","url":null,"abstract":"As a nonlinear dimension reduction algorithm,Gaussian process latent variable model(GPLVM) has been widely applied in pattern recognition and computer vision for its capability in dealing with small size and high-dimensional samples.As GPLVM can discover low-dimensional manifolds in high-dimensional data given only a small number of samples,a new SAR target recognition method was proposed,in which a modified GPLVM was used for feature extraction and Gaussian process classification was employed as the classifier.In GPLVM,the likelihood was optimized by using the scaled conjugate gradient.In order to avoid the noise effect to gradient estimate and overcome the disadvantage that the performance is severely affected by the step length,the immune clone selection algorithm based GPLVM was developed for target feature extraction where the immune clonal selection algorithm characterized by rapid convergence to global optimum was utilized to improve the performance.The experimental results show that the method not only reduces the dimension but also gets higher accuracy.","PeriodicalId":50181,"journal":{"name":"红外与毫米波学报","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69889093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-01-01DOI: 10.3724/SP.J.1010.2013.00277
Guo Rui-Fane, Wang Xiuzhen, Sheng Li, Huang Jingfeng
{"title":"Aerosol optical depth determined by integration of the HJ CCD and IRS data","authors":"Guo Rui-Fane, Wang Xiuzhen, Sheng Li, Huang Jingfeng","doi":"10.3724/SP.J.1010.2013.00277","DOIUrl":"https://doi.org/10.3724/SP.J.1010.2013.00277","url":null,"abstract":"","PeriodicalId":50181,"journal":{"name":"红外与毫米波学报","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69889205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-01-01DOI: 10.3724/sp.j.1010.2013.00160
Chen Li
For samples with distinguishable echoes in detected transmission pulses,we mainly use the phase difference between the detected pulses to extract their refraction indices by transmission terahertz time-domain spectroscopy.Specifically,there are two methods.The first one requires the reference pulse and the first terahertz pulse transmitted through the sample;the second one requires the terahertz pulse transmitted through the sample and the second transmitted pulse after two reflections in the sample.However,in practice,there exists an angle between the incident terahertz beam and the surface normal of the sample.Yet,this angle is not easy to measure.So,in calculation we usually ignore this angle,which often causes error in the extracted refractive indices.In addition,this error is related with the selected method.In this article,after analyzing deviations of the refractive indices resulting from the angle when using the two methods,we propose a method to correct the extracting refractive indices.Our method could theoretically eliminate errors that are caused by the angle.Experiments further prove that this correction method is effective.
{"title":"Extraction of refractive indices of materials through transmission terahertz time-domain spectroscopy","authors":"Chen Li","doi":"10.3724/sp.j.1010.2013.00160","DOIUrl":"https://doi.org/10.3724/sp.j.1010.2013.00160","url":null,"abstract":"For samples with distinguishable echoes in detected transmission pulses,we mainly use the phase difference between the detected pulses to extract their refraction indices by transmission terahertz time-domain spectroscopy.Specifically,there are two methods.The first one requires the reference pulse and the first terahertz pulse transmitted through the sample;the second one requires the terahertz pulse transmitted through the sample and the second transmitted pulse after two reflections in the sample.However,in practice,there exists an angle between the incident terahertz beam and the surface normal of the sample.Yet,this angle is not easy to measure.So,in calculation we usually ignore this angle,which often causes error in the extracted refractive indices.In addition,this error is related with the selected method.In this article,after analyzing deviations of the refractive indices resulting from the angle when using the two methods,we propose a method to correct the extracting refractive indices.Our method could theoretically eliminate errors that are caused by the angle.Experiments further prove that this correction method is effective.","PeriodicalId":50181,"journal":{"name":"红外与毫米波学报","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69888818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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