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Journals >
Acta Optica Sinica >
Volume 40 >
Issue 1 >
Page 0111027 > Article
Acta Optica Sinica
Vol. 40, Issue 1, 0111027 (2020)
Synthetic-Aperture Occlusion Removal Algorithm Using Microlens Array
Wentong Qian
1、2
, hui Li
1、2、3、*
, and Yuntao Wu
1、2
Author Affiliations
1
School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan, Hubei 430205, China
2
Hubei Key Laboratory of Intelligent Robot, Wuhan, Hubei 430205, China
3
School of Chemistry and Chemical Engineering, Huazhong University of Science & Technology, Wuhan, Hubei 430074, China;
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DOI:
10.3788/AOS202040.0111027
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Wentong Qian, hui Li, Yuntao Wu. Synthetic-Aperture Occlusion Removal Algorithm Using Microlens Array[J]. Acta Optica Sinica, 2020, 40(1): 0111027
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Fig. 1.
Flow chart of synthetic-aperture occlusion removal algorithm based on microlens array
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Fig. 2.
Light field sampling based on microlens array
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Fig. 3.
Principle of refocusing
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Fig. 4.
Scene diagram
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Fig. 5.
Original image
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Fig. 6.
Processing images of algorithm for each step. (a) Sampling image of microlens; (b) binary extracted occlusion grid; (c) result without using synthetic aperture; (d) occlusion removal result
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Fig. 7.
Results of three algorithms. (a) Microlens synthetic aperture algorithm; (b) multi-cue fusion extraction depth algorithm; (c) prior information matching based algorithm
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Fig. 8.
Images processed by three algorithms. (a)-(c) Binarization images of Figs. 7(a)-(c); (d)-(f) contour extraction images of Figs. 7(a)-(c)
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Pitch
Radius of curvature
Focal length
Pupil
0.15 mm
2.4 mm
5.2 mm
Chrome
Table 1.
Parameters of MLA150-5C microlens array
Group
Algorithm
Average
gradient
Synthetic aperture of microlens array
0.0476
Group1
Multi-cue fusion extraction depth
[
4
]
0.0212
Base on regional prior information
[
6
]
0.0182
Synthetic aperture of microlens array
0.0324
Group2
Multi-cue fusion extraction depth
[
4
]
0.0238
Base on regional prior information
[
6
]
0.0129
Synthetic aperture of microlens array
0.0387
Group3
Multi-cue fusion extraction depth
[
4
]
0.0232
Base on regional prior information
[
6
]
0.0202
Table 2.
Average gradient value of results of three algorithms
Group
Algorithm
Brenner
Tenengrad
SMD
SMD2
Energy
Synthetic aperture of microlens array
21.638
346.2426
187.6392
4.8237
102.392
Group1
Multi-cue fusion extraction depth
[
4
]
17.2057
297.1573
121.8329
4.7923
82.4373
Base on regional prior information
[
6
]
9.1939
240.0381
83.2398
3.4908
42.9048
Synthetic aperture of microlens array
32.814
392.8423
239.8478
5.2394
124.324
Group2
Multi-cue fusion extraction depth
[
4
]
28.932
242.7176
131.2366
4.3082
58.6362
Base on regional prior information
[
6
]
8.2309
224.8539
78.4905
2.0745
39.7248
Synthetic aperture of microlens array
27.8409
279.8045
95.7356
6.0139
97.4584
Group3
Multi-cue fusion extraction depth
[
4
]
15.897
239.7401
82.3147
5.2253
61.4399
Base on regional prior information
[
6
]
9.2347
134.5629
63.4759
4.8269
57.2825
Table 3.
Comparison of image qualities obtained by different algorithms
Abstract
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Wentong Qian, hui Li, Yuntao Wu. Synthetic-Aperture Occlusion Removal Algorithm Using Microlens Array[J]. Acta Optica Sinica, 2020, 40(1): 0111027
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Paper Information
Category: Special Issue on Computational Optical Imaging
Received: Sep. 2, 2019
Accepted: Oct. 21, 2019
Published Online: Jan. 2, 2020
The Author Email: Li hui (lihui00317@163.com)
DOI:
10.3788/AOS202040.0111027
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