RAW Image

RAW image processing focuses on leveraging the unprocessed sensor data captured by cameras to improve various computer vision tasks and image quality. Current research emphasizes developing efficient algorithms, often employing generative adversarial networks (GANs) and diffusion models, to reconstruct RAW images, remove artifacts like reflections, and enhance low-light images, often without requiring precise camera pose information. These advancements aim to overcome limitations of traditional image signal processing (ISP) pipelines by optimizing directly for downstream applications like object detection and novel view synthesis, leading to improved performance and potentially more efficient image representation. The resulting improvements in image quality and computational efficiency have significant implications for applications ranging from mobile photography to autonomous driving.