Computational Neuromorphic Imaging

Computational neuromorphic imaging brings together event-cameras, neuromorphic sensors, and SPAD arrays to capture visual information inspired by biological vision systems. These unconventional sensors provide unique data representations, but their integration into broader optical and neuromorphic computing frameworks has been slowed by the lack of comprehensive design and processing tools. Despite recent progress, important gaps remain in understanding how to fully exploit their capabilities across diverse applications.This Research Topic aims to address these challenges by fostering collaboration across neuromorphic engineering, computational imaging, optics, and neuroscience. We welcome both fundamental and applied research that explores sensor theory, develops optical models and computational methods, and advances hardware or processing approaches to support robust neuromorphic imaging.We invite articles including, but not limited to:• Neuromorphic optics and design for event-cameras, such as point spread function engineering and coded aperture approaches• New applications of neuromorphic sensing, including phase imaging, spectral imaging, optical communication, and depth sensing• Computational and signal-processing frameworks for event-based data, including real-time neuromorphic implementations• Bio-inspired and unconventional approaches, such as non-imaging optics, active closed-loop sensing, on-board sensor processing, sensor fusion, or novel sensor designsSubmissions should employ event-based or SPAD sensors, avoid reducing event-data to frames unless justified, and consider optical elements beyond simple pinhole camera models. We particularly encourage submissions that highlight neuromorphic principles in sensing, computation, or hardware integration, rather than purely device-level or materials-focused studies. By advancing neuromorphic principles in sensing and computation, this Topic seeks to accelerate the integration of event-based systems into imaging and embedded platforms, bridging artificial and biological paradigms of vision. Topic editors: Nimrod Kruger, Shuangming Yang, Abderazek Ben Abdallah, Alexandre Marcireau, Shuo Zhu Source: https://www.frontiersin.org/research-topics/74694/computational-neuromorphic-imaging