Abstract: The paper has firstly discussed how a right wavelet base can be chosen，and decomposes the SAR image and optical image using the lifting scheme wavelet.Then，the low-frequency images are integrated with the weighted average ways after the SAR low-frequency image is filtered using the regional average means.In order to restrain the speckle noise，the paper focuses on the high-frequency images fusion，and presents a kind of the fusion methods that the windows can be changed according to the noise features，which can make the targets detection and recognition well.Finally，the fusion image is used to extract the features.The result shows that the fusion image is better than the original SAR image for the feature extraction.

摘要： 首先研究了图像融合小波基的选区，并利用提升小波技术分别对合成孔径雷达图像和光学遥感图像进行小波提升分解；然后，对分解后的SAR低频分量进行邻域平均，再与光学图像的低频分量进行加权平均；为了抑制SAR图像斑点噪声的影响，重点研究了高频分量的融合方法，并提出了一种依据斑点噪声特征变化而自适应地改变融合窗口的方法，该方法提高了SAR图像的目标解译和识别能力；最后，使用融合前后的SAR图像进行图像的目标检测，结果表明，融合后的图像能够明显抑制SAR斑点噪声影响，使SAR图像目标检测的效果更佳。