Computational Photography

Computational photography leverages software algorithms to enhance image capture and processing beyond the limitations of traditional camera hardware. Current research heavily focuses on improving image quality in challenging conditions, such as low light and high dynamic range scenes, using deep learning models like neural networks and diffusion models to address issues like denoising, HDR reconstruction, and flare removal. These advancements are driven by the increasing availability of high-resolution sensors and the need for improved image quality in mobile and augmented reality applications, leading to significant improvements in image fidelity and creative possibilities for both professionals and casual users.