Texture Filter

Texture filtering aims to enhance or modify image textures for various applications, including image super-resolution, rendering, and medical image analysis. Current research focuses on developing efficient algorithms, such as those employing stochastic sampling, Gaussian pyramids, and dual-branch neural networks with implicit self-texture enhancement, to achieve accurate and artifact-free results across different image types and scales. These advancements improve image quality and enable new capabilities in fields like computer graphics and medical imaging, particularly in handling high-resolution or arbitrary-scale data where traditional methods struggle. The development of robust and efficient texture filtering techniques is crucial for advancing these fields.