Research on image random matrix modeling and stylized rendering algorithm for painting color learning

Abstract In recent years, the widespread adoption of image capture equipment and advances in image-based computer graphics have made the extraction and application of image structure information, such as gradient fields and lines, a key focus in the field of image processing. Nowadays, most mobile devices have relatively good shooting functions, so people’s demands for multimedia information processing are becoming stronger and stronger. In this study, an importance-driven picture composition method combining various rendering styles is proposed. The importance of each pixel in the picture is estimated based on image saliency or specified by user interaction. This method combines various rendering styles such as color desaturation, line rendering, edge preserving blur and contrast enhancement, and is suitable for image, video, 3D scene and even mixed reality scene. Highlighting the importance of image structure analysis, this study explores innovative methods to enhance the visual quality of augmented reality and stylization algorithms for images and videos. By delving into various rendering techniques, such as color desaturation and line rendering, it aims to significantly improve both the aesthetic appeal and functionality of digital media across diverse platforms, thereby meeting the growing demands for advanced multimedia processing.