Design of Remote Sensing Image Multi-Dimensional Visualization Fusion System Based on Visual Communication

In recent years, 3D image reconstruction technology has become a hot topic in image processing technology. In response to the problems of slow imaging speed, poor imaging accuracy, and poor imaging quality in existing imaging methods, this project proposes a new method for imaging using visual information. This article proposes a method of using visual communication technology to achieve visual fusion of multi-dimensional remote sensing images, which solves the problem of image boundaries not being well matched using conventional methods. The CABAC encoder is used to achieve collaborative work between data and control processes, thereby obtaining feedback information. On this basis, a DSP based remote sensing image output and display system was designed, which achieved effective conversion of remote sensing image information and data, and accelerated the system’s computational speed. This project plans to use a dimensionality reduction method to extract the main feature components in remote sensing images and eliminate redundant dimensions; Using self-organizing neural networks for multidimensional mapping of images; Using visual communication technology to perform multi-dimensional reconstruction of images. On this basis, a visual fusion method based on multidimensional data is proposed. The experimental results show that compared with conventional methods, the images obtained by this method have good consistency and certain regularity, which can meet the needs of relevant work.