基于混合像元分解的水体遥感图像去云法

Cloud-Moving of Water RS Image Based on Mixed Pixel Model

大型内陆水体的遥感图像中往往存在着不均匀薄云或者是气溶胶的影响,由于种种原因,传统的大气辐射校正算法无法消除这种不均匀影响,这就给遥感图像的大气校正带来了很大困难。由于水体属于低反射率地物,这种薄云或者气溶胶的不均匀性带来的误差,极大地降低了水体遥感图像的信噪比,进而影响水体信息遥感提取精度。根据部分太湖地区的遥感图像和地面实测数据,作者以一种新的思路来尝试解决这个问题。该方法充分考虑了水气环境的特点,把水体像元光谱看作水、污染物和气溶胶(薄云)等光谱的混和。基于混合像元模型,该方法有效地消除了薄云和气溶胶的影响,可使我们通过遥感手段更加精确地提取水质信息。

There are always some uneven aerosol or thin cloud effects in the remote sensing image of largescale inland water. These uneven effects bring great difficulty to atmospheric radiant correction of remote sensing images in such regions. Furthermore, because the water is the object with low reflectivity, these uneven effects bring large errors to the water information inversion by remote sensing technology. For some reasons, it is some times impossible for us to use traditional atmospheric radiant correction algorithms（ such as MODTRAN or 6S software） to reduce such effects. With some remote sensing images and ground collecting data in Taihu Lake in China, an important inland water research place of Chinese remote sensing scholars, the authors use a new method to resolve this problem. This method considers the optical characteristics of water-atmosphere environment carefully, assumes each pixel＇ s spectrum is the mixed result of water, pollutant and aerosol or thin cloud, for the optical property of Taihu Lake＇s remote sensing images is determined by water, pollutant and aerosol or thin cloud. Based on Mixed Pixel Model, this method reduces the effects of aerosol and thin cloud effectively. After the process of this method, we can get more veracious water quality information from remote sensing images. In author＇s test, to the same remote sensing inversion model, this method can increase 5 percent precision.