The standard deviation of the central Pacific sea surface temperature anomaly （SSTA） during the period from October to February shows that the central Pacific SSTA variation is primarily due to the occurrence of the...The standard deviation of the central Pacific sea surface temperature anomaly （SSTA） during the period from October to February shows that the central Pacific SSTA variation is primarily due to the occurrence of the Central Pacific E1 Nifio （CP-E1 Nifio） and has a connection with the subtropical air-sea interaction in the northeastern Pacific. After removing the influence of the Eastern Pacific E1 Nifio, an S-EOF analysis is conducted and the leading mode shows a clear seasonal SSTA evolving from the subtropical northeastern Pacific to the tropical central Pacific with a quasi-biennial period. The initial subtropical SSTA is generated by the wind speed decrease and surface heat flux increase due to a north Pacific anomalous cyclone. Such subtropical SSTA can further influence the establishment of the SSTA in the tropical central Pacific via the wind-evaporation-SST （WES） feedback. After established, the central equatorial Pacific SSTA can be strengthened by the zonal advective feedback and thermocline feedback, and develop into CP-E1 Nifio. However, as the thermocline feedback increases the SSTA cooling after the mature phase, the heat flux loss and the reversed zonal advective feedback can cause the phase transition of CP-EI Nifio. Along with the wind stress variability, the recharge （discharge） process occurs in the central （eastern） equatorial Pacific and such a process causes the phase consistency between the thermocline depth and SST anomalies, which presents a contrast to the original recharge/discharge theory.展开更多
针对红外与可见光图像难以提取特征点实现配准的问题,提出一种基于边缘结构特征的红外与可见光图像配准算法。首先通过优化的显著性算法增强红外图像的结构特征;其次利用相位一致性提取红外和可见光图像的稳定边缘结构;然后提取边缘结构...针对红外与可见光图像难以提取特征点实现配准的问题,提出一种基于边缘结构特征的红外与可见光图像配准算法。首先通过优化的显著性算法增强红外图像的结构特征;其次利用相位一致性提取红外和可见光图像的稳定边缘结构;然后提取边缘结构的ORB(oriented FAST and rotated BRIEF)特征点;最后结合KNN(K-nearest neighbor)算法和余弦相似度对匹配特征点进行筛选,并应用RANSAC(random sample consensus)算法进行提纯。实验表明,该算法能够克服灰度差异的影响,具有较高的配准精度和效率,有助于实现红外与可见光图像的配准。展开更多
目的全景图像的质量评价和传输、处理过程并不是在同一个空间进行的,传统的评价算法无法准确地反映用户在观察球面场景时产生的真实感受,针对观察空间与处理空间不一致的问题,本文提出一种基于相位一致性的全参考全景图像质量评价模型...目的全景图像的质量评价和传输、处理过程并不是在同一个空间进行的,传统的评价算法无法准确地反映用户在观察球面场景时产生的真实感受,针对观察空间与处理空间不一致的问题,本文提出一种基于相位一致性的全参考全景图像质量评价模型。方法将平面图像进行全景加权,使得平面上的特征能准确反映球面空间质量畸变。采用相位一致性互信息的相似度获取参考图像和失真图像的结构相似度。接着,利用相位一致性局部熵的相似度反映参考图像和失真图像的纹理相似度。将两部分相似度融合可得全景图像的客观质量分数。结果实验在全景质量评价数据集OIQA(omnidirectional image quality assessment)上进行,在原始图像中引入4种不同类型的失真,将提出的算法与6种主流算法进行性能对比,比较了基于相位信息的一致性互信息和一致性局部熵,以及评价标准依据4项指标。实验结果表明,相比于现有的6种全景图像质量评估算法,该算法在PLCC(Pearson linear correlation coefficient)和SRCC(Spearman rank order correlation coefficient)指标上比WS-SSIM(weighted-to-spherically-uniform structural similarity)算法高出0.4左右,并且在RMSE(root of mean square error)上低0.9左右,4项指标最优,能够获得更好的拟合效果。结论本文算法解决了观察空间和映射空间不一致的问题,并且融合了基于人眼感知的多尺度互信息相似度和局部熵相似度,获得与人眼感知更为一致的客观分数,评价效果更为准确,更加符合人眼视觉特征。展开更多
基金supported by the National Basic Research Program of China(973Program:2012CB955604)National Natural Science Foundation of China(Nos.40975038and40830106)+5 种基金the CMA Program(GYHY200906008)the financial support provided by the China Scholarship Counciljointly supported by the 973 Program of China(2010CB950404)DOE grant DE-SC0005110National Science Foundation(NSF)grants ATM1034798NOAA grand NA10OAR4310200
文摘The standard deviation of the central Pacific sea surface temperature anomaly （SSTA） during the period from October to February shows that the central Pacific SSTA variation is primarily due to the occurrence of the Central Pacific E1 Nifio （CP-E1 Nifio） and has a connection with the subtropical air-sea interaction in the northeastern Pacific. After removing the influence of the Eastern Pacific E1 Nifio, an S-EOF analysis is conducted and the leading mode shows a clear seasonal SSTA evolving from the subtropical northeastern Pacific to the tropical central Pacific with a quasi-biennial period. The initial subtropical SSTA is generated by the wind speed decrease and surface heat flux increase due to a north Pacific anomalous cyclone. Such subtropical SSTA can further influence the establishment of the SSTA in the tropical central Pacific via the wind-evaporation-SST （WES） feedback. After established, the central equatorial Pacific SSTA can be strengthened by the zonal advective feedback and thermocline feedback, and develop into CP-E1 Nifio. However, as the thermocline feedback increases the SSTA cooling after the mature phase, the heat flux loss and the reversed zonal advective feedback can cause the phase transition of CP-EI Nifio. Along with the wind stress variability, the recharge （discharge） process occurs in the central （eastern） equatorial Pacific and such a process causes the phase consistency between the thermocline depth and SST anomalies, which presents a contrast to the original recharge/discharge theory.
文摘针对红外与可见光图像难以提取特征点实现配准的问题,提出一种基于边缘结构特征的红外与可见光图像配准算法。首先通过优化的显著性算法增强红外图像的结构特征;其次利用相位一致性提取红外和可见光图像的稳定边缘结构;然后提取边缘结构的ORB(oriented FAST and rotated BRIEF)特征点;最后结合KNN(K-nearest neighbor)算法和余弦相似度对匹配特征点进行筛选,并应用RANSAC(random sample consensus)算法进行提纯。实验表明,该算法能够克服灰度差异的影响,具有较高的配准精度和效率,有助于实现红外与可见光图像的配准。
文摘目的全景图像的质量评价和传输、处理过程并不是在同一个空间进行的,传统的评价算法无法准确地反映用户在观察球面场景时产生的真实感受,针对观察空间与处理空间不一致的问题,本文提出一种基于相位一致性的全参考全景图像质量评价模型。方法将平面图像进行全景加权,使得平面上的特征能准确反映球面空间质量畸变。采用相位一致性互信息的相似度获取参考图像和失真图像的结构相似度。接着,利用相位一致性局部熵的相似度反映参考图像和失真图像的纹理相似度。将两部分相似度融合可得全景图像的客观质量分数。结果实验在全景质量评价数据集OIQA(omnidirectional image quality assessment)上进行,在原始图像中引入4种不同类型的失真,将提出的算法与6种主流算法进行性能对比,比较了基于相位信息的一致性互信息和一致性局部熵,以及评价标准依据4项指标。实验结果表明,相比于现有的6种全景图像质量评估算法,该算法在PLCC(Pearson linear correlation coefficient)和SRCC(Spearman rank order correlation coefficient)指标上比WS-SSIM(weighted-to-spherically-uniform structural similarity)算法高出0.4左右,并且在RMSE(root of mean square error)上低0.9左右,4项指标最优,能够获得更好的拟合效果。结论本文算法解决了观察空间和映射空间不一致的问题,并且融合了基于人眼感知的多尺度互信息相似度和局部熵相似度,获得与人眼感知更为一致的客观分数,评价效果更为准确,更加符合人眼视觉特征。
