Dynamic Visual Communication Image Framing of Graphic Design in a Virtual Reality Environment

This paper explores dynamic visual communication image framing for graphic design based on virtual reality algorithms; it defines corresponding feature representations by delineating layers of pixels, elements, relationships, planes, and applications; and it investigates methods for quantifying geometric features, perceptual features, and style features. The contents include extraction methods for element colors, calculation methods for layout perceptual features and color-matching perceptual features, and pairwise comparison methods for style features. By overfitting the distribution of geometric features in the data, the model can predict the probability density distribution of features such as element position and color under specific conditions to support the generation of flat images. To construct a prediction model, the sampling method of features, the model optimization method, and the data learning strategy are investigated. This thesis involves the design and implementation of a lossless/near-lossless compression system for high-frame-rate gaze camera image data, which is faced with the technical problems of high fidelity and strong real-time and reliable compression. The image single-frame lossless/near-loss-free compression ratio is generally low, and the compression ratio can be improved by using the correlation between image frames. In this paper, we study the application of lossless compression between image frames, the efficient computing structure of FPGA, and an onboard compression system.