Application of Wireless Network Visual Communication Technology in Fuzzy Image Target Classification Detection

Fuzzy image target classification detection plays an important role in image processing. Traditional classification detection methods are easily affected by environmental and equipment factors, and there are certain limitations in classification accuracy and real-time performance. In order to improve the performance of fuzzy image target classification detection and image processing, this paper combines wireless network visual communication technology and utilizes multi node collaborative processing to achieve fuzzy image information processing. To verify its effectiveness, this article compares it with traditional deep learning (DL) methods. In the experimental analysis, it was found that compared to the DL method, the average accuracy of fuzzy image classification under wireless network visual communication technology improved by 9.46%. The conclusion indicates that wireless network visual communication technology can help improve the real-time performance and classification effect of blurred image targets, and can promote the intelligent development of image processing technology.