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[Editor's Pick] Current Optics and Photonics Vol. 5 no. 5 (2021 October)

사무국 hit 1376 date 2021-10-28

Absolute Depth Estimation Based on a Sharpness-assessment Algorithm for a Camera with an Asymmetric Aperture

Beomjun Kim, Daerak Heo, Woonchan Moon, and Joonku Hahn *

School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Korea

 

Current Optics and Photonics  Vol. 5 No.5 (2021 October) pp. 514-523
DOI: https://doi.org/10.3807/COPP.2021.5.5.514

 


 

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Fig. 1  Defocus model. (a) Geometry of the camera, and (b) the radius of the CoC when half of the aperture size is 7 mm.

 

 

 

Keywords: Coded aperture, Depth estimation, Image reconstruction
OCIS codes: (100.2000) Digital image processing; (100.3008) Image recognition, algorithms and filters; (100.3020) Image reconstruction-restoration; (120.3940) Metrology; (170.1630) Coded aperture imaging
 
Abstract
Methods for absolute depth estimation have received lots of interest, and most algorithms are concerned about how to minimize the difference between an input defocused image and an estimated defocused image. These approaches may increase the complexity of the algorithms to calculate the defocused image from the estimation of the focused image. In this paper, we present a new method to recover depth of scene based on a sharpness-assessment algorithm. The proposed algorithm estimates the depth of scene by calculating the sharpness of deconvolved images with a specific point-spread function (PSF). While most depth estimation studies evaluate depth of the scene only behind a focal plane, the proposed method evaluates a broad depth range both nearer and farther than the focal plane. This is accomplished using an asymmetric aperture, so the PSF at a position nearer than the focal plane is different from that at a position farther than the focal plane. From the image taken with a focal plane of 160 cm, the depth of object over the broad range from 60 to 350 cm is estimated at 10 cm resolution. With an asymmetric aperture, we demonstrate the feasibility of the sharpness-assessment algorithm to recover absolute depth of scene from a single defocused image.