小波变换与图像融合方法在遥感图像处理中的应用

依据小波变换理论,分析得出了图像经多层小波变换后,低层的细节系数频率高于高层细节系数,近似系数的频率最低。遥感图像景物的频率较高,云雾频率较低,高层的细节系数和近似系数包含了云雾信息,因此要提高图像的清晰度,就必须减少高层细节系数和近似系数,增大低层细节系数,去除云雾。为减少处理过程中信息量的丢失,将原图像和处理结果融合。实验表明,该方法能有效地去除云雾。

Application of Wavelet Transformation and Image Fusion to Remote Sensing Image Processing

It is concluded that after the digital image is decomposed with wavelet,the frequency of detail coefficients in low levels is higher than that in high levels,and the frequency of approximate coefficients is the lowest.In remote sensing images the frequency of thin cloud and mist is lower than that of sceneries.Thus,detail coefficients in high levels and approximate coefficients comprise cloud and mist.By increasing the detail coefficients of lower levels,and decreasing those of higher ones and approximate coefficients,the goal for removing the cloud and mist is achieved.In order to avoid the loss of information,the original image and the result image are fused.It is proved that this algorithm is effective.