摘要
针对NPP/VIIRS影像含有短暂光源和背景噪声的问题,研究了月度影像的辐射特征,提出了多时相夜光遥感影像校正方法。该方法采用峰值特征化放大影像的辐射差异,通过卷积运算区分稳定像元与异常像元,结合最大熵阈值自适应滤波分割了卷积边界的混淆噪声。试验结果表明,该方法修正了原始影像的异常波动,剔除了异常像元,影像拟合经济数据的能力明显提升,弥补了夜光数据微观小尺度研究的缺失,可为社会经济数据动态评估提供新的途径。
To solve the problem of ephemeral lights source and background noise for NPP/VIIRS images, the multi-temporal nighttime light remote sensing images calibration method is proposed based on the radiation characteristics of monthly images. The radiation difference of the images is amplified by the spike characterization. The high-pass convolution operation is used to distinguish the stable pixel from the abnormal pixel. On the basis of this, an adaptive threshold segmentation method called the maximum entropy is used to resegment the aliasing noise at the convolution boundary. Through analysis of experimental results, the abnormal fluctuation of the original image is corrected, and the abnormal pixels are eliminated. After calibration, the correlation between VIIRS data and quarterly economic data is stronger. The lack of micro-scale research on nighttime light remote sensing data is compensated, and the dynamic assessment for socio-economic data is provided with new ways.
作者
李明峰
蔡炜珩
LI Mingfeng;CAI Weiheng(School of Geomatics Science and Technology, Nanjing Tech University, Nanjing 211816, China)
出处
《测绘通报》
CSCD
北大核心
2019年第7期122-126,共5页
Bulletin of Surveying and Mapping
基金
南京市科技计划项目(201716027)
江苏省重点研发计划项目(BE2015698)
关键词
NPP/VIIRS
影像校正
最大熵阈值
结果评价
夜光遥感
NPP/VIIRS
image calibration
maximum entropy thresholds
result evaluation
nighttime light remote sensing
