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Search Results: 1 - 10 of 392813 matches for " <br>赵永强 "
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Method of Stokes Images Calculation Based on Adaptive Unsubsample Lifting Scheme

Zhao YongJiang,Pan Quan,Zhang HongCai,<br>,潘泉,张洪才
光子学报 , 2005,
Abstract: 根据成像偏振探测中stokes参数图像获取的原理和方法,分析了传统求取stokes参数图像方法在保留图像细节信息和处理输入图像微小平移等方面的不足,在此基础上提出了基于自适应平移不变小波分解的stokes参数图像求取方法,并用无下采样的提升框架来执行平移不变小波分解以提高算法的灵活性和计算速度.针对不同的stokes参数图像求取方法,用均值、方差、熵、边界能量对融合结果进行评价和分析.通过仿真,表明本文方法提高了stokes参数图像的质量并改善了stokes参数图像计算方法对输入图像平移的敏感性。
Preparation and catalytic properties of Lax Cel-xMnO/y- AI203 catalyst for catalytic combustion of toluene

Wang Shuai,Zhao Chaocheng,Wang Yongqiang,<br>王帅,朝成,
环境工程学报 , 2012,
Abstract: 为了研究镧、铈2种稀土元素共掺金属氧化物催化剂对甲苯的去除效果,采用等体积浸渍法制备了LaxCe1-xMnO/γ-Al2O3稀土改性催化剂。考察了活性组分负载量、焙烧温度对催化剂催化活性的影响,确定了催化剂的最佳制备工艺。同时对镧、铈两种稀土元素不同原子配比对催化活性的影响进行研究。实验结果表明,LaxCe1-xMnO负载量为12%,催化剂的焙烧温度为450℃,La、Ce物质的量比为4∶1,制得的催化剂催化活性最强,催化效率最高,在6 000 h-1空速下,反应温度为320℃时即可将甲苯气体完全燃烧。运用BET、XRD、SEM、XRF等方法对催化剂的结构进行表征,结果表明,催化剂表面活性组分具有高分散性,氧化物颗粒粒径均一且分散均匀。稀土共掺催化剂与单一稀土改性催化剂相比,活性组分易于负载在载体表面,负载效果有着显著的提高。
Differential compressive correlated imaging

Bai Xu,Li Yong-Qiang,Zhao Sheng-Mei,<br>白旭,,生妹
物理学报 , 2013,
Abstract: Correlated imaging offers great potentiality, with respect to standard imaging, to obtain the imaging of objects located in optically harsh or noisy environment. It can solve the problems which are difficult to solve by conventional imaging techniques. Recently, it has become one of the hot topics in quantum optics. In this paper, we propose a new scheme of correlated imaging with differential correlated imaging based on compressive sensing, named differential compressive correlated imaging. The new scheme takes advantage of the high signal-to-noise ratio of the differential correlated imaging and low-imaging sampling frequency of the compressed sensing technique. In the scheme, we utilize the intensity of the thermal light, which is in line with the Gaussian distribution, as the measurement matrix of compressive sensing. We extract the differential object information as the image object information which could be recovered via orthogonal matching pursuit algorithm with high quality. By numerical simulations, we verify the proposed scheme. Here, we select the two gray-scale images, such as double-slit and NUPT, as well as the two multi-grayscale images (Lena and Boats) as the object. We take sampling 350 times in differential compressive correlated imaging for measurement. The numerical simulation results show that for the above image objects, the average mean-square error (MSE) over 10 times for the differential compressive correlated imaging scheme is reduced by 97.7%, 93.9%, 92.5% and 71.4% respectively with respect to that of the differential correlated imaging scheme. Moreover, compared with the compressive ghost imaging, the MSE value of the same double-slit in CDGI, as well as Lena and Boats under the same conditions, is reduced by 50.4%, 72.9% and 66.8% separately, which indicates that the compressive differential correlated imaging scheme can greatly improve the signal-to-noise ratio of the imaging, and significantly reduce the imaging time.
The Abstraction and Analysis of Fractal Characteristic of Noisy Speech

Bao Yong-qiang,Zhao Li,Zou Cai-rong,<br>包,,邹采荣
电子与信息学报 , 2007,
Abstract: Yong-qiang Zhao Li Zou Cai-rong (Department of Radio Engineering, Southeast University, Nanjing 210096, China) Abstract: According to simple computation, good anti-noise ability and low precision of Katz algorithm and complex computation and good precision of box-counting dimension and correlation dimension, an Improvement fractal algorithm Based on Wave (IBW) is presented and analyzed through the fractal Brown curve and noisy speech according to the characteristic of the box dimension and Katz dimension. The theory analyse and experiment show that IBW-FD has lower computation and higher precision than Katz dimension and box-counting dimension. IBW-FD also has stronger ability of anti-noise and distinguish Gaussian noise and speech than the others. It shows that IBW-FD is the good speech fractal algorithm because of low complexity, good precision and nice anti-noise ability.
Anomaly Target Detection in Hyperspectral Imagery Based on Band Subset Fusion by Fuzzy Integral

Di Wei,Pan Quan,Zhao Yong-qiang,He Lin,<br>邸韡,潘泉,,贺霖
电子与信息学报 , 2008,
Abstract: An anomaly target detection method based on the high correlation band subsets and fuzzy integral fusion is presented to deal with detecting unknown target in unknown background for hyperspectral imagery. Original hyperspectral data is divided into several continuous band subsets according to the high correlation within the subset. Applying nonparametric kernel density estimation to the RX detector output of each subset to obtain its probability density function (pdf), and a nonparametric fuzzy membership function is constructed; based on the eigenvalues in spectral dimension, a target signal-noise-ratio is defined to measure the degree of importance of detection result from each subset; finally, decision fusion is implemented through Sugeno fuzzy integral method. Experiments on visible/near-infrared OMIS-I hyperspectral imagery justify the effectiveness of the algorithm.
Anomaly Detection in Multi-Band Spectral Imagery Based on Multiple-Detector Maximum Entropy Fusion

DI Wei,PAN Quan,HE Lin,ZHAO Yong-qiang,<br>邸韡,潘泉,,贺霖
光子学报 , 2007,
Abstract: Anomaly detection in multi-band spectral imagery using single detector has great deficiency due to the model limitation,thus a multiple-detector fusion algorithm is proposed in this paper for this problem.Several different anomaly detectors are selected for obtaining pilot detection results,then a nonparametric method called Kernel Density Estimation(KDE) with bandwidth adjusted adaptively is used to estimate the Probability Density Function(PDF) statistics of the output of each individual detector,which preserves the long-tail behavior of multi-band spectral imagery to avoid the model error.The obtained probabilistic information are then transformed to a space with standard Gaussian marginal distribution,in which optimal probabilistic fusion of multi-detector on the decision level is accomplished utilizing a modeled joint distribution under maximum entropy principle.Target detection is finally achieved by likelihood function test in the original data space.Experimental results on EPS-A aerial multi-band spectral imagery demonstrate the effectiveness of the proposed algorithm.
Study of Adaptive Multi-band Polarization Image Fusion

ZHAO Yong-qiang,PAN Quan,ZHANG Hong-cai,<br>,潘泉,张洪才
光子学报 , 2007,
Abstract: To remove the clutter efficiently and detect the objects accurately,the information presented by multi-band polarization images should be combined.An adaptive weighting multi-band polarization images fusion method is proposed based on the false color mapping and the degree of linear polarization entropy to combine the information.The characters of object and background and the principles of multi-band imaging polarization are used in this method.At the same time,the relation between objects' spectral and polarization information,the information difference contained in polarization images in different band,the relations among Stokes' images in same band,and the information relation between object and background in the degree of linear polarization(DoLP) image are all used in this method.The background clutter is removed through combing Stokes'images and DoLP image in different band.In final simulation,this fusion method is used in different multi-band polarization images,the fusion results and evaluation index show that the background is removed efficiently.
A New Spectral and Panchromatic Images Fusion Method

ZHAO Yong-qiang,PAN Quan,ZHANG Hong-cai,<br>,潘泉,张洪才
光子学报 , 2007,
Abstract: To detect the object efficiently,the difference information presented by spectral images and detail information contained in panchromatic images are combined.A new false color mapping and wavelet integrated approach is presented,and is used to fuse the panchromatic image and spectral images.The contrast between object and background is enhanced through fusing common and distinctive information by false color mapping.Then false color image and panchromatic image are fused by IHS and wavelet transform to retain more detail information.The fusion results and evaluation index show that this algorithm can enhance the visibility of certain details and preserve the contrast of different materials.It also implies that the investigated approach can eventually be applied in object detection and identification.
Classification of Spectropolarimetric Imagery Based on Fuzzy Cluster and Evidence Theory

WANG Dao-rong,ZHAO Yong-qiang,PAN Quan,<br>王道荣,,潘泉
光子学报 , 2007,
Abstract: 为了将光谱偏振信息用于物质分类,提出了一种无监督聚类融合算法.算法结合偏振信息的特性,首先对Stokes参量中的非偏振光强参量、线偏振度参量、偏振角参量进行无监督模糊c均值聚类(FuzzyC-mean,FCM),利用目标表面的偏振特性以及聚类结果分配置信指派,然后对这些置信指派进行加权融合.仿真实验表明了算法的有效性.
Development of a novel photoelectrocatalytic reactor and its reaction kinetics

An Hui,Zhao Chaocheng,Wang Dan,Wang Yongqiang,<br>安慧,朝成,王丹,
环境工程学报 , 2011,
Abstract: A new type of photoelectrocatalytic reactor was developed and the degradation kinetics of wastewater simulated by PEG-2000(0.5 g/L) was studied.The removal of COD from wastewater by electrolysis,photocatalysis and photoelectrocatalysis is zero-order reaction under different external bias,initial pH values,aeration and light intensity,and the reaction occur in the reactor has obvious photoelectric synergies in terms of kinetics.The photoelectrocatalytic reaction of different initial concentrations of wastewa...
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