Multisensor image fusion could improve system performances such as detection, tracking, and identification greatly. In this paper, a long distance target detection approach is presented based on multisensor image features fusion. This method extracts two different features from visual and infrared (IR) image sequences respectively to detect regions of motion information content. Temporal change feature is extracted from the visual image sequence using temporal decomposition based on wavelet, which reflects the dynamical content variation at a pixel at any time. And correlation features between local regions are extracted from IR image sequence to distinguish regions with potential moving targets. All these features are merged into a multi-dimensional space and the support vector machine is trained to select regions that have the potential target at each pixel location. The method is robust and feasible to detect long distance targets in clutter background scene.