Synthetic aperture radar (SAR) sensors can work at all times and under all weather conditions, but SAR images are less intuitive and more difficult to understand. To complement advantages of optical and SAR sensors, a technique of image translation is put forward. Firstly, the definition of remote sensing image translation is presented. Then, some specific solutions for image understanding, and object transformation which are considered as key steps for image translation are proposed. Feature extraction, Support Vector Machine classification, and sample-based texture synthesis algorithms are adopted to translate typical classes of SAR data into optical images. Finally, two kinds of SAR images with different resolution are translated into Landsat TM and GeoEye images respectively, and the translated result could be applied to fill the blanks in those incomplete optical images. Overall, the research indicates that the proposed techniques of image translation from SAR to optical data are rational and effective.