Computational Imaging and Vision Systems
Computational Imaging and Vision Systems merge physics, optics, AI, and signal processing to extend human and machine perception far beyond traditional imaging. Intelligent algorithms reconstruct images from sparse, noisy, or multimodal data, enabling imaging through scattering media, low-light conditions, or at microscopic scales. Computer vision systems recognize objects, activities, gestures, and environmental context, supporting robotics, autonomous vehicles, medical imaging, and scientific analysis. In medical domains, computational imaging reveals tumors, vascular structures, and molecular signatures invisible to classical techniques. Vision models integrate multimodal input-RGB, depth, hyperspectral, thermal-to create richer representations. Research unites physics, neuroscience, photonics, computer graphics, and machine learning. Emerging frontiers include neural rendering, holographic imaging, neuromorphic vision sensors, and event-based cameras. These systems enable machines to see, understand, and act in the physical world with unprecedented fidelity.