High performance imaging in parallel cameras is a worldwide challenge in computational optics studies. However, the existing solutions are suffering from a fundamental contradiction between the field of view (FOV), resolution and bandwidth, in which system speed and FOV decrease as system scale increases. Inspired by the compound eyes of mantis shrimp and zoom cameras, here we break these bottlenecks by proposing a deep learning-based parallel (DLBP) camera, with an 8-μrad instantaneous FOV and 4 × computational zoom at 30 frames per second. Using the DLBP camera, the snapshot of 30-MPs images is captured at 30 fps, leading to orders-of-magnitude reductions in system complexity and costs. Instead of directly capturing photography with large scale, our interactive-zoom platform operates to enhance resolution using deep learning. The proposed end-to-end model mainly consists of multiple convolution layers, attention layers and deconvolution layer, which preserves more detailed information that the image reconstructs in real time compared with the famous super-resolution methods, and it can be applied to any similar system without any modification. Benefiting from computational zoom without any additional drive and optical component, the DLBP camera provides unprecedented-competitive advantages in improving zoom response time (~ 100 ×) over the comparison systems. Herein, with the experimental system described in this work, the DLBP camera provides a novel strategy to solve the inherent contradiction among FOV, resolution and bandwidth.

We propose a multi-view 2D/3D switchable display by using cylindrical liquid crystal (LC) lens array with a low operating voltage and fast response time. The cylindrical LC lens array is composed of three parts: the LC layer, a top-plane indium tin oxide (ITO) electrode, and bottom periodic strip ITO electrodes. In the voltage-off state, the cylindrical LC lens array is equivalent to a transparent glass substrate and the viewers can see a clear 2D image. In the 3D mode, the cylindrical LC lens array can be used as a cylindrical lens array under a suitable operating voltage. As a result, the 2D and 3D images can be switched according to the state of the cylindrical LC lens array. The experimental result shows that the 2D/3D switchable display with the cylindrical LC lens array has a wider viewing angle, has no moiré pattern, and is much thinner compared to the other 2D/3D switchable display devices.

Extending the depth of field (DOF) is especially essential in thick and 3D sample imaging. However, it's difficult to achieve both large DOF and high resolution in a zoom microscope. Currently, the use of optical sectioning to expand DOF still has the problem of inconstant magnification. Here, we develop an extended the depth of field (EDOF) and zoom microscope, which can realize EDOF with constant magnification and high resolution. Besides, the proposed microscope can achieve optical axial scanning at different NA and magnifications in real time without any mechanical movement. The proposed varifocal lens is employed to realize optical axial scanning, zooming, and keeping constant magnification when extending the DOF. Experimental results show that the proposed microscope can realize a continuous optical zoom of 10–40×, NA from 0.14 to 0.54, and the DOF of microscope can be extended to 1.2 mm.

The conventional electrowetting lens usually has one tunable liquid-liquid (L-L) interface. The shape of L-L interface is deformed to get variable focal length due to electrowetting effect. However, contact angle saturation of the L-L interface is an unavoidable problem which prevents focal length from further changing. Here, we demonstrate an optofluidic lens based on electrowetting liquid piston. The proposed lens has two connected chambers, the piston chamber and the lens chamber to form a closed-loop fluidic system. The electrowetting liquid piston can generate clockwise and counter-clockwise liquid flows, which can make the L-L interface convex and concave. To prove the concept, we fabricate an optofluidic device whose shortest negative and positive focal lengths are ~−17.9 mm and ~18 mm with 5 mm aperture, respectively. The proposed optofluidic lens has large tunable focal length range. Widespread application of such an adaptive lens is foreseeable.

The conventional microscope has discrete magnification and slow response time in zoom process, which is difficult to capture the dynamic activity of the live specimen. We demonstrate an adaptive microscope employing a tunable objective and a tunable eyepiece with large zooming range. The tunable objective consists of three glass lenses and four electrowetting liquid lenses. The tunable eyepiece consists of an achromatic eyepiece and an electrowetting liquid lens. The focal point between the objective and the eyepiece is designed to be tunable, which are controlled by voltages. Thus, the tuning range is relatively large. We fabricate the adaptive microscope and observe the specimen. In the experiment, the magnification of the microscope changes continuously from ~ 59.1 × to ~ 159.2 × , and the largest numerical aperture is ~ 0.212. The tunable eyepiece can release the back focal length of the tunable objective, which increases the zoom range of the microscope. No mechanical movement is required and the aberrations can be corrected over a wide wavelength range. Thus, the proposed adaptive microscope has a potential application in biological research and clinical medical examination.

Optical edge detection is a crucial optical analog computing method in fundamental artificial intelligence, machine vision, and image recognition, owing to its advantages of parallel processing, high computing speed, and low energy consumption. Field‐of‐view‐tunable edge detection is particularly significant for detecting a broader range of objects, enhancing both practicality and flexibility. In this work, a novel approach—adaptive optical spatial differentiation is proposed for field‐of‐view‐tunable edge detection. This method improves the ability to acquire spatial information and facilitates edge detection over a wider angular range. The adaptive optical spatial differentiation meta‐device relies on two core components: the spatial differentiation dielectric metasurface and the adaptive liquid prism. The meta‐device is shown to function as a highly efficient (≈85%) isotropic spatial differentiator, operating across the entire visible spectrum (400 to 700 nm) within a wide‐angle object space, expanding up to 4.5 times the original field of view. The proposed scheme presents new opportunities for efficient, flexible, high‐capacity integrated data processing and imaging devices. And simultaneously provides a novel optical analog computing architecture for the next generation of wide field‐of‐view phase contrast microscopy.