Lensless Imaging and Computational Sensing

Dear Colleagues,

Recent advancements in the semiconductor industry have inspired a revolution in compact sensors and computational platforms, creating a paradigm shift from lens-based imaging and sensing to computational imaging and sensing. In extreme cases, computational imaging systems forgo traditional optical hardware including imaging lenses, instead relying on computation to retrieve the relevant imaging information. By eliminating bulky, compound optics, such systems can become compact, cost-effective, and portable, expanding access to imaging and sensing technologies, especially for low-resource settings. Additionally, these computational imaging and sensing systems can take advantage of recent advances in machine learning to infer meaningful information from their nontraditional acquisition hardware. Moreover, the availability of such machine learning tools has led to the creation of data-driven co-design of sensing hardware and software, ushering a new era in sensors designs that present application-specific performance advantages. In this Special Issue of Sensors, we wish to provide a collection of important advances regarding applications of biomedical, chemical, and environmental computational imaging and sensing with focus on (but not limited to) novel design of lens-less imaging or sensing hardware, image processing, and machine learning algorithms for lens-free imaging and sensing, data-driven sensor design, and applications in biomedicine, spectroscopy, and environmental monitoring.

Prof. Dr. Aydogan Ozcan
Prof. Dr. Yair Rivenson
Dr. Yichen Wu
Dr. Zachary Ballard
Guest Editors

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