This study proposes a high-speed image rotation estimation algorithm based on correlation filtering (GPCF) to estimate the camera rotation caused by carrier pose variations. The proposed algorithm uses correlation filtering rather than the correlation operation used in the gray projection method for rotation estimation. The accuracy and robustness of the algorithm are greatly enhanced by introducing a circular shift matrix to increase the number of negative samples. Additionally, a noise-to-signal ratio formula is established to quantify the impact of noise on the rotation estimation. Compared to the gray projection method, both theoretical analysis and experiments reveal that the GPCF can estimate the rotation of image sequences in real time with greater accuracy and reliability.