Abstract: A real-time image feature tracking algorithm based on visual communication effect is proposed to address the issues of low extraction accuracy and poor tracking performance in real-time tracking of multi frame film and television images. By calculating the likelihood function of candidate target states, effective targets in multiple film and television images are obtained, and unnecessary information such as noise and artifacts in the images are removed through visual communication enhancement processing to improve the recognizability of effective targets. Considering the real-time tracking requirements of multi frame film and television images, after multi frame film and television image enhancement, particle swarm optimization algorithm is used to weight the features of multi frame film and television images, improve the weight of salient features, effectively highlight the tracking target, and achieve real-time tracking of multi frame film and television image features. The experimental results show that after processing with the proposed method, the signal-to-noise ratio of the image can reach 45 dB, and the position of the tracked target is relatively consistent with the original marked position. And the target recognition rate, recall rate, and comprehensive evaluation index are all maintained above 0. 9. It is demoustrated that the proposed method can filter out the interference of target image background and surrounding clutter, accurately obtain target feature points, and achieve real-time feature tracking of multiple film and television images. 

Key words: visual communication, multiple frame images, sparse function, wavelet transform, image tracking