Image Formation

Image formation research focuses on understanding and modeling the process by which light interacts with objects and is captured by sensors, aiming to improve image quality and enable advanced image processing tasks. Current research emphasizes incorporating physically-based models into deep learning architectures, such as neural radiance fields and diffusion models, to address challenges like underwater imaging, motion blur, and low-light conditions. These advancements are driving improvements in areas like 3D reconstruction, video deblurring, and high-dynamic range imaging, with significant implications for fields ranging from microscopy to autonomous navigation. Furthermore, information theory is being increasingly applied to optimize the design and evaluation of imaging systems.