Based on previously reported work, we propose a new method for calibrating image plate(IP) scanners, offering greater flexibility and convenience, which can be extended to the calibration tasks of various scanner mode...Based on previously reported work, we propose a new method for calibrating image plate(IP) scanners, offering greater flexibility and convenience, which can be extended to the calibration tasks of various scanner models. This method was applied to calibrate the sensitivity of a GE Typhoon FLA 7000 scanner. Additionally, we performed a calibration of the spontaneous signal attenuation behavior for BAS-MS, BAS-SR, and BAS-TR type IPs under the 20±1℃ environmental conditions, and observed significant signal carrier diffusion behavior in BAS-MS IP. The calibration results lay a foundation for further research on the interaction between ultra-short, ultra-intense lasers and matter.展开更多
With the diversified development of big data,detection and precision guidance technologies,electromagnetic(EM)functional materials and devices serving multiple spectrums have become a hot topic.Exploring the multispec...With the diversified development of big data,detection and precision guidance technologies,electromagnetic(EM)functional materials and devices serving multiple spectrums have become a hot topic.Exploring the multispectral response of materials is a challenging and meaningful scientific question.In this study,MXene/TiO_(2)hybrids with tunable conduction loss and polarization relaxation are fabricated by in situ atomic reconstruction engineering.More importantly,MXene/TiO_(2)hybrids exhibit adjustable spectral responses in the GHz,infrared and visible spectrums,and several EM devices are constructed based on this.An antenna array provides excellent EM energy harvesting in multiple microwave bands,with|S11|up to−63.2 dB,and can be tuned by the degree of bending.An ultra-wideband bandpass filter realizes a passband of about 5.4 GHz and effectively suppresses the transmission of EM signals in the stopband.An infrared stealth device has an emissivity of less than 0.2 in the infrared spectrum at wavelengths of 6-14μm.This work can provide new inspiration for the design and development of multifunctional,multi-spectrum EM devices.展开更多
Based on diverse landforms, the correlation between soil organic matter content and multi-spectral band of remote sensing image was analyzed in this pa- per. In addition, the inversion models were built for the soil o...Based on diverse landforms, the correlation between soil organic matter content and multi-spectral band of remote sensing image was analyzed in this pa- per. In addition, the inversion models were built for the soil organic matter content in different landforms. The results showed that the spectral reflectance was nega- tively related to soil organic matter content; linear regression analysis of remove was performed throughout the bands using SPSS. When the inversion models were built based on all the bands, better fitting effect was obtained. The precision of in- version models built based on different landforms was higher than those built re- gardless landforms. Compared with the actual value, the identification level of soil organic matter content was 91 65% under the allowable error was 7%. It indicated that the extraction of soil organic matter with inversion model that was built based on different landforrrs was feasible with higher precision.展开更多
In order to overcome the shortcomings that the reconstructed spectral reflectance may be negative when using the classic principal component analysis (PCA)to reduce the dimensions of the multi-spectral data, a nonne...In order to overcome the shortcomings that the reconstructed spectral reflectance may be negative when using the classic principal component analysis (PCA)to reduce the dimensions of the multi-spectral data, a nonnegative constrained principal component analysis method is proposed to construct a low-dimensional multi-spectral space and accomplish the conversion between the new constructed space and the multispectral space. First, the reason behind the negative data is analyzed and a nonnegative constraint is imposed on the classic PCA. Then a set of nonnegative linear independence weight vectors of principal components is obtained, by which a lowdimensional space is constructed. Finally, a nonlinear optimization technique is used to determine the projection vectors of the high-dimensional multi-spectral data in the constructed space. Experimental results show that the proposed method can keep the reconstructed spectral data in [ 0, 1 ]. The precision of the space created by the proposed method is equivalent to or even higher than that by the PCA.展开更多
[Objective] The aim of this study was to extract effective feature bands of damaged rice leaves by planthoppers to make identification and classification rapidly from great amounts of imaging spectral data. [Method] T...[Objective] The aim of this study was to extract effective feature bands of damaged rice leaves by planthoppers to make identification and classification rapidly from great amounts of imaging spectral data. [Method] The experiment, using multi-spectral imaging system, acquired the multi-spectral images of damaged rice leaves from band 400 to 720 nm by interval of 5 nm. [Result] According to the principle of band index, it was calculated that the bands at 515, 510, 710, 555, 630, 535, 505, 530 and 595 nm were having high band index value with rich information and little correlation. Furthermore, the experiment used two classification methods and calcu-lated the classification accuracy higher than 90.00% for feature bands and ful bands of damaged rice leaves by planthoppers respectively. [Conclusion] It can be con-cluded that these bands can be considered as effective feature bands to identify damaged rice leaves by planthoppers quickly from a large scale of crops.展开更多
Histogram of collinear gradient-enhanced coding (HCGEC), a robust key point descriptor for multi-spectral image matching, is proposed. The HCGEC mainly encodes rough structures within an image and suppresses detaile...Histogram of collinear gradient-enhanced coding (HCGEC), a robust key point descriptor for multi-spectral image matching, is proposed. The HCGEC mainly encodes rough structures within an image and suppresses detailed textural information, which is desirable in multi-spectral image matching. Experiments on two multi-spectral data sets demonstrate that the proposed descriptor can yield significantly better results than some state-of- the-art descriptors.展开更多
Image fusion is performed between one band of multi-spectral image and two bands of hyperspectral image to produce fused image with the same spatial resolution as source multi-spectral image and the same spectral reso...Image fusion is performed between one band of multi-spectral image and two bands of hyperspectral image to produce fused image with the same spatial resolution as source multi-spectral image and the same spectral resolution as source hyperspeetral image. According to the characteristics and 3-Dimensional (3-D) feature analysis of multi-spectral and hyperspectral image data volume, the new fusion approach using 3-D wavelet based method is proposed. This approach is composed of four major procedures: Spatial and spectral resampling, 3-D wavelet transform, wavelet coefficient integration and 3-D inverse wavelet transform. Especially, a novel method, Ratio Image Based Spectral Resampling (RIBSR)method, is proposed to accomplish data resampling in spectral domain by utilizing the property of ratio image. And a new fusion rule, Average and Substitution (A&S) rule, is employed as the fusion rule to accomplish wavelet coefficient integration. Experimental results illustrate that the fusion approach using 3-D wavelet transform can utilize both spatial and spectral characteristics of source images more adequately and produce fused image with higher quality and fewer artifacts than fusion approach using 2-D wavelet transform. It is also revealed that RIBSR method is capable of interpolating the missing data more effectively and correctly, and A&S rule can integrate coefficients of source images in 3-D wavelet domain to preserve both spatial and spectral features of source images more properly.展开更多
To monitor growth and predict the yield of rice over a large area, the chlorophyll contents in the rice canopy were estimated using the unmanned aerial vehicle(UAV) remote sensing technology. In this work, multi-spect...To monitor growth and predict the yield of rice over a large area, the chlorophyll contents in the rice canopy were estimated using the unmanned aerial vehicle(UAV) remote sensing technology. In this work, multi-spectral image information of the rice crop was obtained using a 6-channel multi-spectral camera mounted on a fixed wing UAV, which was flown 600 m above the ground, between 11: 00-14: 00 on a sunny day in summer. The measured chlorophyll values were collected as sample sets. The s-REP index was screened out to estimate chlorophyll contents through the analysis of six kinds of spectral indexes of chlorophyll estimated capacity. An inversion model of the chlorophyll contents was then built using the least square support vector regression(LS-SVR)algorithm, with calibration and prediction R-square values of 0.89 and 0.83, respectively. Finally, remote sensing mapping for a UAV image of the Fangzheng County Dexter Rice Planting Park was accomplished using the inversion model. The inversion and measured values were then compared using regression fitting. R-square and root-mean-square error of the fitting model were 0.79 and 2.39,respectively. The results demonstrated that accurate estimation of rice-canopy chlorophyll contents was feasible using the LS-SVR inversion model developed using the s-REP vegetation index.展开更多
Evaluation of the impact of herbicides on maize was done through multi- spectral and multi-modal imaging and multi-spectral fluorescence imaging combined with statistical methods. Spectra containing 13 wavelengths ran...Evaluation of the impact of herbicides on maize was done through multi- spectral and multi-modal imaging and multi-spectral fluorescence imaging combined with statistical methods. Spectra containing 13 wavelengths ranging from 375 nm to 940 nm were derived from multi-spectral images in transmission, reflection and scattering mode and fluorescence images obtained using high-pass filters (F450 nm, F500 nm, F550 nm, F600 nm, F650 nm) on control maize samples and maize samples treated with Herbextra herbicide were used. The appearance of the spectra allowed us to characterize the effect of the herbicide on the maize pigment concentration. The fluorescence images allowed us to track the fate of absorbed energy and through PLS-DA and SVM-DA to discriminate the two leaf categories with very low error rates for the test, i.e. 4.9% and 2% respectively. The results of this technique can be used in the context of precision agriculture.展开更多
Considering the problem of traditional cervical cancer detection method that brings high false negative rate (FNR) and high false positive rate (FPR), a new abnormal cervical cells detection method of multi-spectr...Considering the problem of traditional cervical cancer detection method that brings high false negative rate (FNR) and high false positive rate (FPR), a new abnormal cervical cells detection method of multi-spectral Pap smear is proposed in this thesis, on the basis of multi-spectral microscopic imaging technology and computer automotive recognition technology. At first, image in a specific wave band is segmented according to the relationship between intensity and spectrum of each pixel. Then, multi-spectral features of each pixel are extracted making use of improved cosine correlation analysis (CCA) algorithm. Combined with the characteristic of each cell's area, final definition is made. Experiments have proved the new approach could identify abnormal cells efficiently as well as lower FNR and FPR.展开更多
基金supported by the Nuclear Industry Academician Fund, the National Natural Science Foundation of China (Grant No. 1220051312)Young Talents Fund of China National Nuclear Corporation (Grant No. FY212406000901)。
文摘Based on previously reported work, we propose a new method for calibrating image plate(IP) scanners, offering greater flexibility and convenience, which can be extended to the calibration tasks of various scanner models. This method was applied to calibrate the sensitivity of a GE Typhoon FLA 7000 scanner. Additionally, we performed a calibration of the spontaneous signal attenuation behavior for BAS-MS, BAS-SR, and BAS-TR type IPs under the 20±1℃ environmental conditions, and observed significant signal carrier diffusion behavior in BAS-MS IP. The calibration results lay a foundation for further research on the interaction between ultra-short, ultra-intense lasers and matter.
基金supported by the National Natural Science Foundation of China(Grant Nos.52373280,52177014,51977009,52273257).
文摘With the diversified development of big data,detection and precision guidance technologies,electromagnetic(EM)functional materials and devices serving multiple spectrums have become a hot topic.Exploring the multispectral response of materials is a challenging and meaningful scientific question.In this study,MXene/TiO_(2)hybrids with tunable conduction loss and polarization relaxation are fabricated by in situ atomic reconstruction engineering.More importantly,MXene/TiO_(2)hybrids exhibit adjustable spectral responses in the GHz,infrared and visible spectrums,and several EM devices are constructed based on this.An antenna array provides excellent EM energy harvesting in multiple microwave bands,with|S11|up to−63.2 dB,and can be tuned by the degree of bending.An ultra-wideband bandpass filter realizes a passband of about 5.4 GHz and effectively suppresses the transmission of EM signals in the stopband.An infrared stealth device has an emissivity of less than 0.2 in the infrared spectrum at wavelengths of 6-14μm.This work can provide new inspiration for the design and development of multifunctional,multi-spectrum EM devices.
文摘Based on diverse landforms, the correlation between soil organic matter content and multi-spectral band of remote sensing image was analyzed in this pa- per. In addition, the inversion models were built for the soil organic matter content in different landforms. The results showed that the spectral reflectance was nega- tively related to soil organic matter content; linear regression analysis of remove was performed throughout the bands using SPSS. When the inversion models were built based on all the bands, better fitting effect was obtained. The precision of in- version models built based on different landforms was higher than those built re- gardless landforms. Compared with the actual value, the identification level of soil organic matter content was 91 65% under the allowable error was 7%. It indicated that the extraction of soil organic matter with inversion model that was built based on different landforrrs was feasible with higher precision.
基金The Pre-Research Foundation of National Ministries andCommissions (No9140A16050109DZ01)the Scientific Research Program of the Education Department of Shanxi Province (No09JK701)
文摘In order to overcome the shortcomings that the reconstructed spectral reflectance may be negative when using the classic principal component analysis (PCA)to reduce the dimensions of the multi-spectral data, a nonnegative constrained principal component analysis method is proposed to construct a low-dimensional multi-spectral space and accomplish the conversion between the new constructed space and the multispectral space. First, the reason behind the negative data is analyzed and a nonnegative constraint is imposed on the classic PCA. Then a set of nonnegative linear independence weight vectors of principal components is obtained, by which a lowdimensional space is constructed. Finally, a nonlinear optimization technique is used to determine the projection vectors of the high-dimensional multi-spectral data in the constructed space. Experimental results show that the proposed method can keep the reconstructed spectral data in [ 0, 1 ]. The precision of the space created by the proposed method is equivalent to or even higher than that by the PCA.
基金Supported by National Natural Science Foundation of China under Grant(No.60968001,61168003)Natural Science Foundation of Yunnan Province under Grant(No.2011FZ079,2009CD047)National Training Programs of Innovation and Entrepreneurship for Undergraduates under Grant(No.201210681005,201310681004)~~
文摘[Objective] The aim of this study was to extract effective feature bands of damaged rice leaves by planthoppers to make identification and classification rapidly from great amounts of imaging spectral data. [Method] The experiment, using multi-spectral imaging system, acquired the multi-spectral images of damaged rice leaves from band 400 to 720 nm by interval of 5 nm. [Result] According to the principle of band index, it was calculated that the bands at 515, 510, 710, 555, 630, 535, 505, 530 and 595 nm were having high band index value with rich information and little correlation. Furthermore, the experiment used two classification methods and calcu-lated the classification accuracy higher than 90.00% for feature bands and ful bands of damaged rice leaves by planthoppers respectively. [Conclusion] It can be con-cluded that these bands can be considered as effective feature bands to identify damaged rice leaves by planthoppers quickly from a large scale of crops.
文摘Histogram of collinear gradient-enhanced coding (HCGEC), a robust key point descriptor for multi-spectral image matching, is proposed. The HCGEC mainly encodes rough structures within an image and suppresses detailed textural information, which is desirable in multi-spectral image matching. Experiments on two multi-spectral data sets demonstrate that the proposed descriptor can yield significantly better results than some state-of- the-art descriptors.
文摘Image fusion is performed between one band of multi-spectral image and two bands of hyperspectral image to produce fused image with the same spatial resolution as source multi-spectral image and the same spectral resolution as source hyperspeetral image. According to the characteristics and 3-Dimensional (3-D) feature analysis of multi-spectral and hyperspectral image data volume, the new fusion approach using 3-D wavelet based method is proposed. This approach is composed of four major procedures: Spatial and spectral resampling, 3-D wavelet transform, wavelet coefficient integration and 3-D inverse wavelet transform. Especially, a novel method, Ratio Image Based Spectral Resampling (RIBSR)method, is proposed to accomplish data resampling in spectral domain by utilizing the property of ratio image. And a new fusion rule, Average and Substitution (A&S) rule, is employed as the fusion rule to accomplish wavelet coefficient integration. Experimental results illustrate that the fusion approach using 3-D wavelet transform can utilize both spatial and spectral characteristics of source images more adequately and produce fused image with higher quality and fewer artifacts than fusion approach using 2-D wavelet transform. It is also revealed that RIBSR method is capable of interpolating the missing data more effectively and correctly, and A&S rule can integrate coefficients of source images in 3-D wavelet domain to preserve both spatial and spectral features of source images more properly.
基金Supported by the National Key R&D Program of China(2016YFD0300610)
文摘To monitor growth and predict the yield of rice over a large area, the chlorophyll contents in the rice canopy were estimated using the unmanned aerial vehicle(UAV) remote sensing technology. In this work, multi-spectral image information of the rice crop was obtained using a 6-channel multi-spectral camera mounted on a fixed wing UAV, which was flown 600 m above the ground, between 11: 00-14: 00 on a sunny day in summer. The measured chlorophyll values were collected as sample sets. The s-REP index was screened out to estimate chlorophyll contents through the analysis of six kinds of spectral indexes of chlorophyll estimated capacity. An inversion model of the chlorophyll contents was then built using the least square support vector regression(LS-SVR)algorithm, with calibration and prediction R-square values of 0.89 and 0.83, respectively. Finally, remote sensing mapping for a UAV image of the Fangzheng County Dexter Rice Planting Park was accomplished using the inversion model. The inversion and measured values were then compared using regression fitting. R-square and root-mean-square error of the fitting model were 0.79 and 2.39,respectively. The results demonstrated that accurate estimation of rice-canopy chlorophyll contents was feasible using the LS-SVR inversion model developed using the s-REP vegetation index.
文摘Evaluation of the impact of herbicides on maize was done through multi- spectral and multi-modal imaging and multi-spectral fluorescence imaging combined with statistical methods. Spectra containing 13 wavelengths ranging from 375 nm to 940 nm were derived from multi-spectral images in transmission, reflection and scattering mode and fluorescence images obtained using high-pass filters (F450 nm, F500 nm, F550 nm, F600 nm, F650 nm) on control maize samples and maize samples treated with Herbextra herbicide were used. The appearance of the spectra allowed us to characterize the effect of the herbicide on the maize pigment concentration. The fluorescence images allowed us to track the fate of absorbed energy and through PLS-DA and SVM-DA to discriminate the two leaf categories with very low error rates for the test, i.e. 4.9% and 2% respectively. The results of this technique can be used in the context of precision agriculture.
基金Supported by Key Project of the Tenth Five-Year Plan of the Ministry of Science and Technology of China (2001BA210A02)
文摘Considering the problem of traditional cervical cancer detection method that brings high false negative rate (FNR) and high false positive rate (FPR), a new abnormal cervical cells detection method of multi-spectral Pap smear is proposed in this thesis, on the basis of multi-spectral microscopic imaging technology and computer automotive recognition technology. At first, image in a specific wave band is segmented according to the relationship between intensity and spectrum of each pixel. Then, multi-spectral features of each pixel are extracted making use of improved cosine correlation analysis (CCA) algorithm. Combined with the characteristic of each cell's area, final definition is made. Experiments have proved the new approach could identify abnormal cells efficiently as well as lower FNR and FPR.