Color Image Denoising

Color image denoising aims to remove noise from digital images while preserving important details, improving image quality and enabling more accurate downstream analysis. Current research focuses on developing efficient and effective denoising algorithms, including those based on deep learning architectures like convolutional neural networks and transformers, as well as physics-informed models that leverage sensor characteristics or physical constraints. These advancements are crucial for various applications, from improving the performance of consumer cameras and sensors to enhancing the accuracy of computer vision systems in robotics and medical imaging. The development of large-scale, high-quality datasets for training and evaluation is also a significant area of ongoing work.