tracking based on correlation filter has become a research hotspot currently. The traditional tracking model trained from circular correlation is sensitive to the pixel arrangement of the target and is difficult to adapt object deformation, but it has good robustness of variety in color of illumination and similar color interference. However, the model based on spatial reliability can adapt to the deformation by establishing the spatial confidence map as the random field constraint of the correlation filter, but it has less robustness for the color change. In order to exert the superiorities of the two tracking methods, the concept of directional reliability is innovative presented and a set of the optimization strategies is proposed to achieve optimal translation estimation of the two tracking models in both the x-axis and y-axis. Comparative results on OTB2013 and OTB2015 show that the method performs favorable against the other state-of-the-art algorithms and can achieve real-time tracking. It has good accuracy and robustness.