Ground based real-time measurement telescopes typically include two sets of optical systems for capture and imaging. When a telescope uses a capture system to track an object in a closed-loop manner， due to the large field of view and low tracking accuracy， the video jitter of the imaging system can be clearly felt， which is not conducive to real-time observation of the object and related scientific experiments. To address the aforementioned issues， this article proposed an electronic image stabilization technology that supports scene switching perception. Firstly， when the object did not appear， the maximum connected region method was used to attempt to extract the object feature region for each frame until it was successfully extracted. Then， for each image， a kernel correlation filter was used to match the features of the previous frame's training model， and the training model was updated. Next， the least squares method was used to fit the object motion trajectory and determine the authenticity of the object through error analysis. Finally， determined whether to use jitter compensation for cropping the current image based on the authenticity of the object. Experimental results indicate that the video processed by this technology has a significant improvement in object stability， the maximum jitter amplitude of adjacent image feature regions decreases from ± 10 pixels to approximately ± 1 pixel， the peak signal-to-noise ratio of reference frames within 50 frames is increased by an average of 4.62 dB； Simultaneously， the algorithm can perceive the object entering and leaving the field of view； The algorithm processing time is less than 2 ms， meeting the online processing requirements. Realize the automation of the image stabilization process for continuous observation of multiple objects， and improve the quality and success rate of related scientific experiments.