摘要
本文在借鉴遥感影像云雾去除相关研究基础上,提出了一种自适应滤波和非线性灰度变换的高分辨率遥感影像薄云雾消除方法,并与现有的几种效果较好的去云雾方法进行了对比研究。结果表明,本文提出的方法不仅能够有效降低薄云雾遮挡干扰影响,而且可以很好地保持原始影像真实的光谱特性,同时针对不同波段地物光谱特性做相应的灰度变换和融合处理,能够在很大程度上减少遥感影像的细节信息的丢失和保持图像的清晰度,是一种有效去除薄云雾覆盖的方法。
There are sometimes some uneven thin cloud-fog effects in the remote sensing images from optical remote sensors, especially in cloudy and rainy areas. A new method based on adaptive filtering and gray-scale transformation was proposed to remove the cloud-fog cover of the high-resolution remote sensing images in this paper. This comprehensive technology program was applied to process the SPOT5 image with heavy thin cloud-fog cover acquired from Zhuhai, China. And to test its superiority, a comparative experiment with two other available methods named homomorphism filter and an approach based on Laplacian enhancement and histogram transformation was carried on. Several objective indicators, such as PSNR （Peak Signal-to Noise Ratio）, average absolute deviation and spectral correlation coefficient （proposed by Li Yuechen ）, were used to evaluate the resulting images. Besides, to verify the general reliability of the framework proposed, more image data from different sensors, such as TM and CMB satellite, in the cloudy and rainy areas were selected for the corresponding experiment. The resuhs indicate that the experimental results for different data source are consistent, which show that the proposed integrated methods can remove the thin cloud-fog cover effectively and maintain the true spectral features of the original image to a large extent. Furthermore, as a result of the application of different parameters of filtering and grayscale transformation for different spectral band, the spatial details and true spectral information are remained as more as possible.
出处
《地球信息科学》
CSCD
北大核心
2009年第3期305-311,共7页
Geo-information Science
基金
民用航天空间应用项目“以国产卫星为主要数据源的珠江三角洲多云多雨地区遥感应用研究”
关键词
自适应滤波
灰度变换
薄云
高分辨率遥感影像
adaptive filtering
thin cloud-fog
gray-scale transformation
high-resolution remote sensing images
