Color Image

Color image processing research focuses on enhancing image quality and extracting meaningful information, addressing challenges like noise, blur, color distortion, and missing data in various contexts (e.g., underwater imaging, low-light conditions). Current research employs advanced techniques such as quaternion-based methods to leverage inter-channel correlations, transformer networks for feature extraction and fusion, and generative adversarial networks for tasks like inpainting and restoration. These advancements improve image quality for applications ranging from medical imaging and remote sensing to autonomous vehicles and artistic image manipulation.