【摘要】 高精度的夜间灯光数据能够有效反映人类空间活动特征,传统的SNPP-VIIRS夜间灯光影像去噪方法容易忽略新增加或消失的有效灯光,且未处理灯光异常值,随着时间推移,去噪误差会逐渐增大。因此,本文提出了利用中值滤波与低阈值去噪相结合的方法过滤SNPP-VIIRS夜间灯光影像中的异常值及背景噪声,并将去噪后的夜间灯光总量与GDP进行相关性分析及精度验证。试验结果表明,通过中值滤波与低阈值去噪结合的方法提取的夜间灯光总量与GDP的相关性优于传统方法,利用该方法建立的模型估算出的亮度值精度更高,证明该方法具有更高的去噪精度。更多还原

【Abstract】 The high precision nighttime lights data can effectively reflect the characteristics of human space activities. The traditional SNPP-VIIRS nighttime lights images denoising method is easy to ignore the newly added or disappeared effective light,and has not dealt with the light outliers. With the passage of time,the denoising error will gradually increase. Therefore,this paper proposes to filter the outliers and background noise of SNPP-VIIRS nighttime lights images using a combination of median filtering and low threshold denoising,and the correlation between the total amount of nighttime light after denoising and GDP is analyzed and the accuracy is verified. Experimental results show that the correlation between the total amount of nighttime light collected by median filtering and low threshold denoising and GDP is superior to the traditional method,and the precision of the brightness estimated by the model established by this method is higher,reflecting that the method has a higher denoising precision.更多还原