In single-frequency precise-point positioning of a satellite,ionosphere delay is one of the most important factors impacting the accuracy. Because of the instability of the ionosphere and uncertainty of its physical p...In single-frequency precise-point positioning of a satellite,ionosphere delay is one of the most important factors impacting the accuracy. Because of the instability of the ionosphere and uncertainty of its physical properties, the positioning accuracy is seriously limited when using a precision-limited model for correction. In order to reduce the error, we propose to introduce some ionosphere parameter for real-time ionosphere-delay estimation by applying various mapping functions. Through calculation with data from the IGS（ International GPS Service） tracking station and comparison among results of using several different models and mapping functions, the feasibility and effectiveness of the new method are verified.展开更多
For a scintillating-fiber array fast-neutron radiography system,a point-spread-function computing model was introduced,and the simulation code was developed. The results of calculation show that fast-neutron radiograp...For a scintillating-fiber array fast-neutron radiography system,a point-spread-function computing model was introduced,and the simulation code was developed. The results of calculation show that fast-neutron radiographs vary with the size of fast neutron sources,the size of fiber cross-section and the imaging geometry. The results suggest that the following qualifications are helpful for a good point spread function: The cross-section of scintillating fibers not greater than 200 μm×200 μm,the size of neutron source as small as a few millimeters,the distance between the source and the scintillating fiber array greater than 1 m,and inspected samples placed as close as possible to the array. The results give suggestions not only to experiment considerations but also to the estimation of spatial resolution for a specific system.展开更多
目的针对运动模糊图像复原中,传统频谱法存在的检测误差大、抗噪性弱及有效检测范围有限等问题,本文提出一种融合高斯拉普拉斯(Laplacian of Gaussian,LoG)滤波与Radon变换的边缘增强频谱分析法,旨在实现点扩散函数(point spread functi...目的针对运动模糊图像复原中,传统频谱法存在的检测误差大、抗噪性弱及有效检测范围有限等问题,本文提出一种融合高斯拉普拉斯(Laplacian of Gaussian,LoG)滤波与Radon变换的边缘增强频谱分析法,旨在实现点扩散函数(point spread function,PSF)参数的精准估计。方法基于脑部MRI仿真运动模糊模型,分析频谱中明暗条纹的分布特征,采用LoG滤波提取频谱亮条纹边缘,抑制中心宽条纹与Gibbs现象导致的干扰,生成保留方向特征的离散边缘点集;利用Radon变换包容非共线点集的抗噪特性(离散边缘点沿角度θ投影时,真实边缘贡献相干叠加,噪声点投影随机抵消),显著提升峰信噪比,进而精准定位模糊角度并计算模糊长度;采用配对t检验,对传统中心亮条纹检测方法与本文方法的PSF参数估计误差进行统计学分析比较。结果本研究方法的角度估计平均误差0.08°,显著低于传统方法的3.28°,长度估计平均误差0.15像素,传统方法为0.88像素,有效角度检测范围由传统方法的±60°扩展到0~180°,且组间误差差异均达极显著水平(P<0.001)。结论本方法通过LoG滤波与Radon变换的协同机制,避免了对中心条纹完整性的依赖,解决了宽条纹导致的检测失效问题,同时有效抑制了噪声和Gibbs现象导致的干扰,显著提高了运动模糊PSF参数估计的精度与鲁棒性,为医学影像运动伪影消除提供可靠的技术基础。展开更多
提出了一种在Bayes概率统计框架下的混合Bayes超分辨率重建算法,该算法采用Huber马尔可夫随机场(Huber Markov random field,HMRF)模型对理想图像进行先验建模,可以较好地突出重建图像的不连续边缘特征信息。实验结果表明,该算法克服了...提出了一种在Bayes概率统计框架下的混合Bayes超分辨率重建算法,该算法采用Huber马尔可夫随机场(Huber Markov random field,HMRF)模型对理想图像进行先验建模,可以较好地突出重建图像的不连续边缘特征信息。实验结果表明,该算法克服了极大后验概率估计(maximum a posteriori,MAP)算法中的若干缺陷,取得了良好的重建结果,图像边缘特征清晰,纹理信息突出。展开更多
基金supported by the National Natural Science Foundation of China(40902081,40774001,40841021)
文摘In single-frequency precise-point positioning of a satellite,ionosphere delay is one of the most important factors impacting the accuracy. Because of the instability of the ionosphere and uncertainty of its physical properties, the positioning accuracy is seriously limited when using a precision-limited model for correction. In order to reduce the error, we propose to introduce some ionosphere parameter for real-time ionosphere-delay estimation by applying various mapping functions. Through calculation with data from the IGS（ International GPS Service） tracking station and comparison among results of using several different models and mapping functions, the feasibility and effectiveness of the new method are verified.
基金Supported by the Foundation of Double-Hundred Talents of China Academy of Engineering Physics (Grant No. 2004R0301)
文摘For a scintillating-fiber array fast-neutron radiography system,a point-spread-function computing model was introduced,and the simulation code was developed. The results of calculation show that fast-neutron radiographs vary with the size of fast neutron sources,the size of fiber cross-section and the imaging geometry. The results suggest that the following qualifications are helpful for a good point spread function: The cross-section of scintillating fibers not greater than 200 μm×200 μm,the size of neutron source as small as a few millimeters,the distance between the source and the scintillating fiber array greater than 1 m,and inspected samples placed as close as possible to the array. The results give suggestions not only to experiment considerations but also to the estimation of spatial resolution for a specific system.
文摘目的针对运动模糊图像复原中,传统频谱法存在的检测误差大、抗噪性弱及有效检测范围有限等问题,本文提出一种融合高斯拉普拉斯(Laplacian of Gaussian,LoG)滤波与Radon变换的边缘增强频谱分析法,旨在实现点扩散函数(point spread function,PSF)参数的精准估计。方法基于脑部MRI仿真运动模糊模型,分析频谱中明暗条纹的分布特征,采用LoG滤波提取频谱亮条纹边缘,抑制中心宽条纹与Gibbs现象导致的干扰,生成保留方向特征的离散边缘点集;利用Radon变换包容非共线点集的抗噪特性(离散边缘点沿角度θ投影时,真实边缘贡献相干叠加,噪声点投影随机抵消),显著提升峰信噪比,进而精准定位模糊角度并计算模糊长度;采用配对t检验,对传统中心亮条纹检测方法与本文方法的PSF参数估计误差进行统计学分析比较。结果本研究方法的角度估计平均误差0.08°,显著低于传统方法的3.28°,长度估计平均误差0.15像素,传统方法为0.88像素,有效角度检测范围由传统方法的±60°扩展到0~180°,且组间误差差异均达极显著水平(P<0.001)。结论本方法通过LoG滤波与Radon变换的协同机制,避免了对中心条纹完整性的依赖,解决了宽条纹导致的检测失效问题,同时有效抑制了噪声和Gibbs现象导致的干扰,显著提高了运动模糊PSF参数估计的精度与鲁棒性,为医学影像运动伪影消除提供可靠的技术基础。
基金国家高技术研究发展计划(863)(the National High-Tech Research and Development Plan of China under Grant No.2006AA012324)航空基金(the Aeronautical Science Foundation No.20060853010)高等院校博士学科点专项科研基金(the China Specialized Research Fundfor the Doctoral Program of Higher Education under Grant No.20040699034)
文摘提出了一种在Bayes概率统计框架下的混合Bayes超分辨率重建算法,该算法采用Huber马尔可夫随机场(Huber Markov random field,HMRF)模型对理想图像进行先验建模,可以较好地突出重建图像的不连续边缘特征信息。实验结果表明,该算法克服了极大后验概率估计(maximum a posteriori,MAP)算法中的若干缺陷,取得了良好的重建结果,图像边缘特征清晰,纹理信息突出。
