Texture Knowledge

Texture knowledge, encompassing both structural patterns and statistical properties of image data, is crucial for various computer vision tasks and understanding human visual perception. Current research focuses on integrating texture information into deep learning models for improved semantic segmentation and image rendering, often employing techniques like contourlet decomposition and texture intensity equalization to extract and leverage these features. Furthermore, studies are exploring how to effectively incorporate texture into dimensionality reduction algorithms for high-dimensional image analysis, and investigating the neural correlates of texture processing in the human brain using methods such as magnetoencephalography and multivariate pattern analysis. These advancements have significant implications for improving the accuracy and efficiency of computer vision systems and furthering our understanding of visual cognition.