Visual Communication Design Method Based on Multimedia Information Processing Technology and Its Application
Affiliation:
1. 1 Art Design College, Henan Institute of Technology , Xinxiang, Henan, 453003 , China
Abstract
Abstract
When the information society has become the mainstream environment, various applications of big data and computers have been popularized in various industries. Multimedia technology has always been a special part of the computer field. In audio, video, image processing, and transmission, multimedia information processing has become the main means to solve the above problems. The performance of this information processing technology is extremely powerful. It can not only process dynamic data but also complete the transmission task in the big data environment. Visual communication design is a way of transmitting information to the masses by using various effects, and it has its advantages in the selection of images, video, text, and other processing technologies. This paper mainly studies the concept, method, and application effect of visual communication design under multimedia information processing. Firstly, the application of multimedia information processing technology in various fields and countries is investigated. Based on the literature analysis and statistics, the advantage tendency of this technology is judged. Starting from the visual functions involved in visual communication, the application effect of the multimedia 3D image processing and rendering communication platform is used. The gray function is used to build the multimedia information processing platform and form a complete and effective evaluation system. Finally, the visual communication design optimized by multimedia processing technology is further analyzed to improve the defects of dynamic images in visual applications and further improve the impact of visual communication design on the masses. The results show that multimedia information processing technology can improve the efficiency of image data processing in visual communication design, and has a good impact on visual communication of dynamic information.
Publisher
Walter de Gruyter GmbH
Subject
Applied Mathematics,Engineering (miscellaneous),Modeling and Simulation,General Computer Science
Reference20 articles.
1. Kishor, A., Chakraborty, C., & Jeberson, W. (2021). Reinforcement learning for medical information processing over heterogeneous networks. Multimedia Tools and Applications, 80(16), 23983-24004. 2. Amit, K., Chinmay, C., & Wilson, J. (2021). Reinforcement learning for medical information processing over heterogeneous networks. Multimedia Tools and Applications, 80(16), 23983-24004. 3. Zhao, H., Liu, Z., Yao, X., & Yang, Q. A. (2021). Machine learning-based sentiment analysis of online product reviews with a novel term weighting and feature selection approach. Information Processing & Management, 58(5), 102656. 4. Zhang, Y. D., Satapathy, S. C., Guttery, D. S., Górriz, J. M., & Wang, S. H. (2021). Improved breast cancer classification through combining graph convolutional network and convolutional neural network. Information Processing & Management, 58(2), 102439. 5. Zhang, S., Liu, H., He, J., Han, S., & Du, X. (2021). A deep bi-directional prediction model for live streaming recommendation. Information Processing & Management, 58(2), 102453.
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