联合散射与统计规律的遥感影像卷云自动校正

卷云广泛存在于大气中，严重阻碍光学遥感对地观测过程，降低了数据的精度与可用性.针对此问题，以卷云检测波段为参考，联合散射与统计规律，提出了一种卷云自动校正方法.方法首先利用散射规律推导出卷云检测波段与待校正波段间的定量关系；进一步地，以卷云检测波段为校正参考基准，联合线性波段统计规律，实现各待校正波段卷云强度的估计与去除.选择多光谱Landsat-8 OLI(Operational land imager)为试验数据对方法有效性和场景适应性进行测试，并进一步拓展至高光谱AVIRIS(Airborne visible infrared imaging spectrometer)和高分五号AHSI(Advanced hyperspectral imager)影像数据.结果表明提出方法可有效去除不同波段的卷云干扰，适用于各类地表覆被类型影像，准确复原降质地表信息，在目视与定量评测方面均有较好表现，可满足定量遥感等应用要求.

Automatic correction of cirrus clouds in remote sensing images based on joint scattering and statistical laws

Cirrus clouds were widely existed in the atmosphere, which seriously hindered the ground observation process of optical remote sensing, and reduced the accuracy and availability of data. An automatic cirrus clouds correction method was proposed, which fully uses the cirrus clouds detection band and couples a scattering law with the band correlation. Firstly, a scattering law was used to quantitatively describe the cirrus clouds intensity and further applied to derive the correlation of cirrus clouds in bands. Then, taking the cirrrus clouds detection band as reference, the band correlation between adjacent bands was mined and coupled with a scattering law to estimate the cirrus clouds intensity accurately in different bands and remove the cirrus clouds. The Landsat-8 operational land imager (OLI) data was selected for experiment to validate the accuracy and adaptability of the method. Moreover, the airborne visible infrared imaging spectrometer (AVIRIS)and GaoFen-5 advanced hyperspectral imager (AHSI)data were further chosen to test the expandation. Results showed that the proposed method could effectively remove the cirrus clouds interference in different bands and was suitable for various scenes, accurately recovered the reduced surface information, had good performance in visual and quantitative evaluation, and could meet the application requirements of quantitative remote sensing.