基于HOT影像优化的遥感影像去雾算法

针对BSHTI和IBSHTI两种算法对卫星影像云雾校正后,地表的色调和纹理等细节缺失严重的问题,提出OIBSHTI算法对IBSHTI算法得出的雾厚度图像进行地表信息削减。通过填洼算法去除暗色区域,并引入纹理和边缘信息等进行优化处理,在彻底去除云雾的同时保留地表的色调和纹理,特别是蓝色或红色建筑物房顶的校正效果较为明显。

Remote Sensing Image Dehazing Algorithm Based on Optimized Image HOT

The algorithms of background suppressed haze thickness index(BSHTI) and improvement background suppressed haze thickness index(IBSHTI) can completely correct the impact of cloud.After the correction by using these two algorithms,the image has serious lack of details,such as the tone and texture information of the surface.To solve these problems,an algorithm of optimized improvement background suppressed haze thickness index(OIB-SHTI) has proposed,which can reduce the surface information of IBSHTI obtained image.The dark regions of IB-SHTI image are eliminated by processing depressions of the proposed algorithm.The texture and edge information (TEI) have introduced to optimize the IBSHTI image.Experiment results show that the surface tones and textures are retained while the influence of cloud is effectively corrected.Especially,the correction effect on the blue or red building roof is obvious.