Titlebook: Coded Optical Imaging; Jinyang Liang Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature

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Coded Ptychographic Imaginghese two approaches can address the intrinsic trade-off between resolution and field of view of an optical system, thereby offering new opportunities for biomedical imaging in the visible light regime. For both approaches, we provide a detailed procedure for implementing ptychographic reconstruction

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Dipole-Spread Function Engineering for Six-Dimensional Super-Resolution Microscopyortex, pixOL, raPol, CHIDO, and MVR DSFs. We also cover common imaging system designs and techniques for implementing engineered DSFs. Finally, we discuss recent biological applications of 6D SMOLM and future challenges for pushing the capabilities and utility of the technology.

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Diffractive Optical Neural Networksation and optical diffraction have been promising to enable new machine learning intelligence and functionality in optical domain and reduce computing energy and resource requirements in electrical domain. In this chapter, the fundamental models to describe and design DONNs are first reviewed. Passi

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Spatiotemporal Phase Aperture Coding for Motion Deblurringmits the exposure time for capturing moving objects, making it challenging to achieve proper exposure. To compensate for this issue, the proposed method utilizes dynamic phase-coding in the lens aperture during image acquisition, which encodes the motion trajectory in an intermediate optical image.