# All-in-Focus Three-Dimensional Reconstruction Based on Edge Matching for Artificial Compound Eye
## 2 Related Work  
In 2001, [PERSON] et al., inspired by the dragonfly's opposition compound eye, proposed a compact imaging system called TOMBO (Thin Observation Module by Bound Optics) [15]. In 2004, [PERSON] et al. proposed another artificial opposition compound eye called APCO (Proposition Compound Eye Objective) [16]. Although APCO has multiple imaging channels, each channel only contains one pixel, which leads to an overall resolution of only  
Figure 4: The overlapped area with adjacent sub-images. (**a**) A sub-image with its four neighboring sub-images. (**b**) The overlapped area with left adjacent sub-image (the white area indicates the overlapped area, and the green area shows the non-overlapped area). (**c**) With upper adjacent sub-image. (**d**) With right adjacent sub-image. (**e**) With bottom adjacent sub-image. Figure 3: The depth map of sub-images with different methods, Different depths are shown in different colors, the color bar is shown on the far right of the image. (**a**) The sub-image for depth estimation. (**b**) The edge depth map. (**c**) The dense depth propagated from edge depth. (**d**) The refined depth map. (**e**) The depth map based on BP [6]. (**f**) The depth map based on Cost Filter [8]. \(130\times 130\). [PERSON] et al. proposed a superposition compound eye system called Cley (Cluster Eye) [17]. In 2007, [PERSON] et al. proposed an artificial neural superposition eye to mimic its bio-prototype [18]. [PERSON] et al. was inspired by a parasite of wasps called Xenos Peckii and proposed the MULTICAM [19]. Each channel of MULTICAM can be seen as a small camera, and the full FOV image of MULTICAM can be reconstructed by the image processing method. In 2010, [PERSON] et al. followed this idea and proposed the eCley system [1]. eCley can achieve a VGA resolution while keeping the overall thickness at 1.4 mm. In 2011, [PERSON] et al. proposed an oCley system [20]. Apart from ACE with plane structure, many curved ACE systems were also proposed to achieve a large FOV. [PERSON] et al. proposed a hemispherical compound eye [21]. [PERSON] et al. proposed an arthropod-inspired camera [22]. [PERSON] et al. proposed the CurvACE (Curved Artificial Compound Eye) [23]. Many other ACE systems can be found in [3; 24; 25; 26]. Although a lot of ACE systems were proposed and researched, the research is mainly focused on the optical imaging, and the related image processing method is not well studied. [PERSON] et al. [27] rearranged pixels of ACE aperture images to reconstruct the high-resolution image for TOMBO. [PERSON] et al. proposed an iterative back-projection method to improve the result [28]. However, these methods reconstruct the image only on a specified distance. [PERSON] et al. proposed a three-dimensional estimation method [29] and then combined the depth map into image reconstruction [30]. [PERSON] et al. [31] proposed a flexible compound-eye-like sensor to detect motion and estimate the proximity. [PERSON] et al. proposed compound-eye sensor with motion hyperacuity in the same year [32], and then compared it with a CCD Camera [33]. [PERSON] et al. used stereo matching and the SIFT feature to estimate the depth of a TOMBO image [34]. [PERSON] et al. proposed a time-stamp-based optic flow ACE sensor for motion detection [35]. [PERSON] et al. proposed an edge detection method for ACE to detect horizontal, vertical, forward diagonal, and backward diagonal edges [36]. [PERSON] et al. proposed a COMPU-EYE system and designed a depth estimation method to reconstruct a high-resolution and sharp image [37]. For eCley, [PERSON] proposed a braiding method to reconstruct the image with a final resolution of \(640\times 480\)[38; 4], but the braiding method can only focus on a specified distance. [PERSON] et al. introduced a depth-related image reconstruction method [39], where the depth of each channel image was obtained by fusing the matching results with four neighboring images. [PERSON] et al.