Application of Multimedia Feature Extraction Technology in the Restoration of Tang Tomb Murals

Through the study of ancient murals, we can get valuable information about the lifestyle, hobbies, history and culture of the ancients. However, due to the influence of human and natural factors, murals often have problems such as cracks, fading and falling off. Traditional repair methods are not only time-consuming and laborious, but also may cause more serious secondary damage during the repair process. Therefore, this paper studies the application of multimedia feature extraction technology in the restoration of Tang tomb murals, aiming at assisting the restoration of murals. Therefore, a real-time feedback method for learning and monitoring of multimedia sensor networks based on linear shift adaptive optimization is proposed, and the optimal deployment model of nodes is constructed. The fusion tracking method of sensor nodes in the cluster is used for multimedia information fusion and two-dimensional entropy feature extraction.