# Retina-like Imaging and Its Applications: A Brief Review
## 2 Principle and Methods
### Methods  
Many researchers have studied the realization of retina-like imaging from hardware and software. The realization based on hardware can be divided into two kinds of approaches: passive and active. Passive retina-like imaging methods selectively collect the target information, and active retina-like imaging methods explore the target information purposively. The two methods realize the retina-like imaging with specially designed  
Figure 2: The sample model of retina-like imaging. sensors. However, the software-based method uses LPT algorithm directly on the Cartesian imaging sensors to simplify the processing procedure. The passive method of retina-like imaging has been used since 1990. [PERSON] et al. [21] designed a retina-like CCD sensor to search for targets in a wide FOV. A total of 30 rings with 64 sectors are present per ring. The size of these 1920 pixels increases form 30 \(\upmu\)m to 412 \(\upmu\)m. In 2000, [PERSON] et al. [22] realized the retina-like CMOS sensors with 8013 pixels located with log-polar algorithm and 845 pixels in the fovea. Compared with CCD, CMOS is more controllable in data storage and easier to interface with microprocessors; thus, it is more suitable for simulating the acquisition of human eye retina information. In 2014, our group [23] used nonuniformity lens array to collect light on the light-sensitive materials with log-polar configuration. This method shifts the difficulty to the lens array design, which makes it more flexible to adjust to different situations. In 2016, the camera array [24] and dual-channel foveated imaging systems [25] were proposed by [PERSON] et al. and [PERSON] et al., respectively. A camera array formed by prisms and cameras combines the advantages of compound eyes and realizes high-resolution fovea and low-redundancy periphery. It reconstructs the super resolution for imaging the center with repeated stack of multiple cameras. The all-reflective, dual-channel foveated imaging system realizes the retina-like variable-resolution imaging with double barrels and double sensors. It is a combination of two different focus imaging systems with common light channels. Compared with a divided camera, it has a compactable structure, but subsequent image processing is needed to form the final image. This method was improved in 2017 by [PERSON] et al. [26]. An imaging system with dual-aperture optics that superimpose two images on a single sensor was designed to enable arbitrary magnification ratios using a relatively simple system. This method fully utilizes the sensor's pixels, which is important in applications where the cost of each pixel is high. In the same year, a micro-lens array was used to form the foveated imaging [27]. A 3D-printed micro-lens with different focus lengths in a 2 \(\times\) 2 arrangement was located directly on the CMOS sensors. It achieves a full FOV of 70\({}^{\circ}\) with an increasing angular resolution of up to two cycles/deg FOV in the center of the image. Different from the methods above, a foveated imaging system with reflective spatial light modulator was proposed by [PERSON] et al. [28]. It corrects the aberration of the region of interest (ROI) while the resolution of the other area is still very low. This method adjusts the fovea location with different phase patterns. In 2019, [PERSON] et al. [29] proposed a foveated imaging system with a liquid crystal lens. This method modulates light selectively with a liquid crystal lens of variable focal length. In 2020, [PERSON], [PERSON] et al. [30] realized the bioinspired, zoom eye-enabled, variable-focus imaging with a deformable polydimethylsiloxane lens array. Similar to the lens of human eyes, it images the target with different distances clearly. Its FOV reaches 180\({}^{\circ}\), and its focal length can be tuned from 3.03 mm to infinity with an angular resolution of 3.86 \(\times\) 10\({}^{-4}\) rad.