In response to the special situation where the near-infrared monocular vision pose measurement system in complex application environments deviates from the preset cooperative target object and cannot complete pose measurement， a monocular vision measurement method based on the random rough surface image around the cooperative target is proposed， as well as a dynamic self-healing method after image damage. By matching and calculating the real-time acquired features of the random rough surface image with the pre stored reference image features， emergency measurement in special situations is completed. At the same time， in order to reduce the impact on the pose measurement accuracy after the pollution or damage of the random rough surface image， real-time computing calculation of the degree of pollution or damage and dynamic self-healing of the reference image features. The experimental results show that the pose measurement accuracy of the random rough surface object is slightly lower than that of the cooperative target object， but it can meet the emergency use needs in special situations and improve the robustness of the measurement system. When the pollution or damage of the random rough surface image reaches 70%， using self-healing processing reduces the azimuth measurement error by more than 72% compared to not doing self-healing processing， verifying the effectiveness of the benchmark image self-healing method.