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国家自然科学基金(40801130)

作品数:2 被引量:11H指数:2
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Monitoring paddy rice phenology using time series MODIS data over Jiangxi Province,China被引量:4
2014年
Paddy rice is one of the most important crops in the world.Accurate estimation and monitoring of paddy rice phenology is necessary for management and yield prediction.Remotely sensed time-series data are essential for estimation of crop phenology stages across large areas.Here,the paddy rice phenological stages(i.e.,transplanting,tillering,heading,and harvesting)were detected in Jiangxi Province,China.A comparison study was conducted using ground observation data from 10 agricultural meteorological stations,collected between 2006 and 2008.The phenological stages were detected using Moderate Resolution Imaging Spectroradiometer(MODIS)time-series enhanced vegetation index(EVI)data.Savitzky-Golay filter and wavelet transform were used to reduce the noise in the time-series EVI data and reconstruct the smoothed EVI time-series profile.Key phenological stages of double-cropping rice were detected using the characteristics of the smoothed EVI profile.The root mean square errors(RMSEs)for each stage were ±10 days around the ground observation data.The results suggest that Savitzky-Golay filter and wavelet transform are promising approaches for reconstructing high-quality EVI time-series data.Moreover,the phenological stages of double-cropping rice could be detected using time-series MODIS EVI data smoothed by Savitzky-Golay filter and wavelet transform.
Li ShihuaXiao JiangtaoNi PingZhang JingWang HongshuWang Jingxian
关键词:PHENOLOGY
非局部联合稀疏近似的超分辨率重建算法被引量:7
2011年
该文结合联合稀疏近似和非局部自相似的概念,提出非局部联合稀疏近似的超分辨率重建方法。该方法将输入图像的跨尺度高、低分辨率图像块统一进行联合稀疏编码,建立它们之间的稀疏关联,并将这种关联作为先验知识来指导图像的超分辨率重建。该文方法保证跨尺度自相似集具有相同的稀疏性模式,能更有效地利用图像的自相似性先验信息,提高算法的自适应性。通过自然图像实验,与其它几种基于学习的超分辨率算法对比,超分辨率效果有较好改善。
李民李世华李小文乐翔
关键词:图像处理超分辨率非局部
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