Perspective Transformation Algorithm for Light Field Image

Jianming Wang; Yiming Mao; Tao Yan; Yuan Liu

doi:10.3788/LOP56.151003

Journals >Laser & Optoelectronics Progress >Volume 56 >Issue 15 >Page 151003 > Article

Laser & Optoelectronics Progress
Vol. 56, Issue 15, 151003 (2019)

Perspective Transformation Algorithm for Light Field Image

Jianming Wang^1、2, Yiming Mao^1、2, Tao Yan^1、2、*, and Yuan Liu^1、2

Author Affiliations

¹ School of Digital Media, Jiangnan University, Wuxi, Jiangsu 214122, China

² Jiangsu Key Laboratory of Media Design and Software Technology, Wuxi, Jiangsu 214122, China

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DOI: 10.3788/LOP56.151003 Cite this Article Set citation alerts

Jianming Wang, Yiming Mao, Tao Yan, Yuan Liu. Perspective Transformation Algorithm for Light Field Image[J]. Laser & Optoelectronics Progress, 2019, 56(15): 151003 Copy Citation Text

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Fig. 1. Perspective transformation model for light field image

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Perspective transformation results of light field image with black holes. (a) Input central subaperture view image; (b) perspective transformation result of single subaperture view image; (c) perspective transformation fusion result of all subaperture view images

Fig. 2. Perspective transformation results of light field image with black holes. (a) Input central subaperture view image; (b) perspective transformation result of single subaperture view image; (c) perspective transformation fusion result of all subaperture view images

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Fig. 3. Light field image restoration results based on disparity priority. (a) Subaperture view image to be restored; (b) subaperture disparity map before restoration; (c) restored subaperture view image; (d) restored subaperture disparity map

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Fig. 4. Restoration order of all subaperture views in light field image

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Fig. 5. Results of light field perspective transformation and restoration. (a1)-(f1) Input central subaperture view images; (a2)-(f2) perspective transformation results; (a3)-(f3) restored perspective transformation results

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Fig. 6. Comparison of light field image perspective transformation results. (a1)-(c1) Results of method in Ref. [8]; (a2)-(c2) results of method in Ref. [9]; (a3)-(c3) results of proposed method; (a4)-(c4) truth images

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Parameter	Fig. 5(a)	Fig. 5(b)	Fig. 5(c)	Fig. 5(d)	Fig. 5(e)	Fig. 5(f)
b /mm	1.00	1.00	1.50	1.12	1.65	0.86
T_x /mm	-20	-20	-30	-60	-45	-50
T_y /mm	0	0	0	0	0	0
T_z /mm	0	0	0	0	0	0
R_x /(°)	0	0	0	1	0.5	0.5
R_y /(°)	0	0.5	0.5	1	0.5	0.5
R_z /(°)	0	0	0	5	-3	-3

Table 1. Parameters for perspective transformation

Parameter	Fig. 5(a)	Fig. 5(b)	Fig. 5(c)	Fig. 5(d)	Fig. 5(e)	Fig. 5(f)
T / s	283.98	286.95	305.79	302.98	298.11	282.24

Table 2. Consuming time of proposed algorithm

Parameter	Method	Fig. 6(a)	Fig. 6(b)	Fig. 6(c)
	Method in Ref. [8]	23.18	22.38	22.72
PSNR	Method in Ref. [9]	26.35	22.06	22.53
	Proposed	35.43	25.69	30.74
	Method inRef. [8]	0.67	0.81	0.79
SSIM	Method in Ref. [9]	0.78	0.81	0.79
	Proposed	0.96	0.89	0.95

Table 3. Quantitative analysis for light field perspective transformation images

Jianming Wang, Yiming Mao, Tao Yan, Yuan Liu. Perspective Transformation Algorithm for Light Field Image[J]. Laser & Optoelectronics Progress, 2019, 56(15): 151003

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