Simulation of Image Restoration Technology on Museum VR Platform Based on Adaptive Segmentation and Wireless Sensor Network

With the development of wireless sensor network (WSN) technology, image restoration technology based on WSN has gradually become a research hotspot. This paper aims to study the image restoration technology based on adaptive segmentation and wireless sensor network, and explore its application in museum VR platform to improve the accuracy and efficiency of image restoration. The image data is transmitted through wireless sensor network, and the collaborative processing ability of sensor nodes is used to restore the image. In this paper, the museum VR platform is built, and the research is simulated and tested. The experimental results show that the image restoration technology based on adaptive segmentation and wireless sensor network has a significant improvement in image quality and recovery speed. Compared with traditional methods, this technology can better maintain the details and texture of the image, and has higher stability and anti-interference ability, which can not only improve the virtual experience of users, but also provide strong support for the protection of cultural relics and digital management.