基于6S模型的遥感影像逐像元大气纠正算法

An algorithm based on 6S model for removing atmospheric effects form satellite imagery pixel by pixel

大气纠正的目的是从遥感影像中去除大气影响,并反演获取地物真实反射率。介绍了一种逐像元对遥感影像进行大气纠正的算法,该算法基于6S(Second Simulation of the Satellite Signal in the Solar Spectrum)大气辐射传输模型计算建立的查找表(look-up table),并利用地面暗目标(dark object)进行陆地气溶胶光学厚度的自动反演,由于气溶胶的分布具有空间连续性,在获取地面暗目标气溶胶光学厚度值后,通过空间插值的方法计算影像中非暗目标像元的气溶胶光学厚度值,经过查找表二次插值计算,逐像元进行大气纠正并获取像元地表反射率值。以Landsat5遥感影像为例,介绍了算法流程,展示了大气纠正的结果。结果显示,利用查找表逐像元大气纠正的算法,能够在一定程度上去除云雾对影像的影响,更加精确的对遥感影像进行大气纠正并获取地物的真实反射率。

The objective of atmospheric correction is to retrieve the surface reflectance from remotely sensed imagery by removing the atmospheric effects. A new algorithm based on the look up table which founded by 6S model was introduced and used to derive the aerosol optical depth and retrieve surface reflectance from a Landsat5 imagery. Dark object algorithm was used to identify the dense dark vegetation and then the aerosol optical depth of those pixels was computed by interpolation from the look-up table automatically. A reverse distance interpolation was applied to all imagery and so every pixels got a aerosol optical depth value. The look-up table was used to derive atmospheric parameters and surface reflectance. The algorithm was applied to the Landsat5 imagery and the result shows that the atmospheric correction effect is good.