The image point feature stability under the Opposite-Movement (OM) and inference conditions is a significant problem in the field of Optoelectronic information. The feature stability problem was researched under the condition when the high speed OM existed between the camera and the scene. First, the principle of the OM blur was analyzed in detail. And then, the stability variation law under the OM blur was analyzed by the experiment and the sifting method of the Harris corner under the OM blur was presented. For the OM blur, the radiant distance of the feature to image center has an important implication on the feature stability. On the basis of traditional Harris corner uncertainty method of Hessian matrix, the radiant distance weighted measure was proposed. The experiment results revealed that, under OM blur condition, the sifting method proposed here could exclude the most unstable feature, and furthermore significantly improve the repeatability of the active feature set.