However, conventional image recognition systems using a flat image sensor array with a multilens optical system and the von-Neumann computing architecture for processing the acquired image data have several limitations such as high system-level complexity, bulky module size, large computing load, and low energy efficiency. [7] Therefore, advanced devices in both image acquisition and image data processing are required. As a result, bio-inspired imaging devices [8][9][10] (i.e., artificial vision) and neuromorphic image processing devices [11][12][13] (i.e., artificial synapse) have received considerable attention (Figure 1).Bio-inspired imaging devices (e.g., bioinspired camera) have been developed for image acquisition. [14] Conventional imaging devices require bulky and heavy optical systems to obtain high-quality visual information. [15] In contrast, natural eyes have a simple and small optical geometry and high-quality image acquisition capability. [16,17] Therefore, bio-inspired artificial vision has been developed by mimicking the unique structural and functional advantage of natural eyes [2,6] (Figure 1a). For example, the chambered eye, typically found in humans and aquatic animals, exhibits a wide field of view, low optical aberration, and facile accommodation with a simple optical system. [16,17] The compound eye has distinctive optical geometries, and such structures offer various useful visual features. [18,19] Neuromorphic computing devices that can efficiently process massive image data acquired from the imaging device have been developed for image data processing. [20][21][22] The conventional von-Neumann architecture, in which the central processing unit and memory unit are separated, is not suitable to efficiently process the massive unstructured image data. [23,24] Therefore, a novel computing device inspired by the human brain (i.e., electronic synapse) has been developed [25,26] (Figure 1b). For example, the memristor crossbar array can efficiently perform vector multiplications. [27] Such a neuromorphic device implements artificial neural networks (ANN) in the hardware and enables efficient parallel processing of image data with low energy consumption. [25] In a previous study, a device that integrates the synaptic device and photodetector in one unit has been reported. [26] Despite recent progress in the hardware of the neuromorphic image data processing devices, such devices still require Remarkable technological developments for efficient image recognition (i.e., image acquisition and image data processing) have been reported in the past decade. Such advances in imaging and image processing technologies have driven significant progress in mobile electronics and machine vision applications. In particular, for image acquisition devices, two types of natural eyes (i.e., chambered and compound eyes) have inspired the development of novel multifunctional imaging devices with unique optical geometries. For image data processing devices, novel computing devices based on memristor crossbar arrays,...
With the rise of mobile robotics, including self-driving automobiles and drones, developing artificial vision for high-contrast and high-acuity imaging in vertically uneven illumination conditions has become an important goal. In such situations, balancing uneven illumination, improving image contrast for facile object detection, and achieving high visual acuity in the main visual fields are key requirements. Meanwhile, in nature, cuttlefish (genus Sepia ) have evolved an eye optimized for vertically uneven illumination conditions, which consists of a W-shaped pupil, a single spherical lens, and a curved retina with a high-density photoreceptor arrangement and polarized light sensitivity. Here, inspired by the cuttlefish eye, we report an artificial vision system consisting of a W-shaped pupil, a single ball lens, a surface-integrated flexible polarizer, and a cylindrical silicon photodiode array with a locally densified pixel arrangement. The W-shaped pupil integrated on the ball lens balances vertically uneven illumination, and the cylindrical silicon photodiode array integrated with the flexible polarizer enables high-contrast and high-acuity imaging.
Over the past few decades, nanowires have arisen as a centerpiece in various fields of application from electronics to photonics, and, recently, even in bio-devices. Vertically aligned nanowires are a particularly decent example of commercially manufacturable nanostructures with regard to its packing fraction and matured fabrication techniques, which is promising for mass-production and low fabrication cost. Here, we track recent advances in vertically aligned nanowires focused in the area of photonics applications. Begin with the core optical properties in nanowires, this review mainly highlights the photonics applications such as light-emitting diodes, lasers, spectral filters, structural coloration and artificial retina using vertically aligned nanowires with the essential fabrication methods based on top-down and bottom-up approaches. Finally, the remaining challenges will be briefly discussed to provide future directions.
Imaging applications based on microlens arrays (MLAs) have a great potential for the depth sensor, wide field-of-view camera and the reconstructed hologram. However, the narrow depth-of-field remains the challenge for accurate, reliable depth estimation. Multifocal microlens array (Mf-MLAs) is perceived as a major breakthrough, but existing fabrication methods are still hindered by the expensive, low-throughput, and dissimilar numerical aperture (NA) of individual lenses due to the multiple steps in the photolithography process. This paper reports the fabrication method of high NA, Mf-MLAs for the extended depth-of-field using single-step photolithography assisted by chemical wet etching. The various lens parameters of Mf-MLAs are manipulated by the multi-sized hole photomask and the wet etch time. Theoretical and experimental results show that the Mf-MLAs have three types of lens with different focal lengths, while maintaining the uniform and high NA irrespective of the lens type. Additionally, we demonstrate the multi-focal plane image acquisition via Mf-MLAs integrated into a microscope.
Vertically oriented semiconductor nanowires (NWs) have been intensely studied in macroscopic perspective due to their attractive applications such as optical filters, photodiodes, and solar cells. However, microscopic photonic phenomena of dense and random NWs have been rarely, and their promising applications have not been explored. Therefore, this article theoretically and experimentally investigates the microscopic photonic event of dense and random NWs using highly selective and sensitive photon sieve (SSPS), which employs highly populated III/V semiconductor NW forests fabricated with a lithography‐free self‐catalyzed growth method. Theoretical analyses reveal that diameter‐dependent and selective photon absorption occurs even for a dense and disordered NW distribution. The engineered growth process affords highly populated NW forests (mean shortest interval = 192.4 nm) comprising NWs with a high aspect ratio (mean aspect ratio = 34.3) and a sufficiently broad diameter distribution to span the visible spectrum and decompose it (mean diameter = 94 nm, standard deviation = 49 nm). Moreover, the SSPS exhibits unique spectral responses to monochromatic light of different wavelengths (correlation coefficients < 0.03) and a high sensitivity with a highest absorptivity of 92.4%. This work indicates SSPSs can be utilized for various applications of artificial photoreceptor, physically unclonable function, and high efficient optoelectronics.
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