An Improved Criminisi Image Inpainting Method Based on Information Entropy and Gradient Factor

Fengsui Wang; Zhengnan Liu; Linjun Fu

doi:10.3788/LOP57.221006

Laser & Optoelectronics Progress, Volume. 57, Issue 22, 221006(2020)

An Improved Criminisi Image Inpainting Method Based on Information Entropy and Gradient Factor

Fengsui Wang^1,2,3、*, Zhengnan Liu^1,2,3, and Linjun Fu^1,2,3

¹Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment, Ministry of Education, Wuhu, Anhui 241000, China

²Anhui Key Laboratory of Electric Drive and Control, Wuhu, Anhui 241000, China

³School of Electrical Engineering, Anhui Polytechnic University, Wuhu, Anhui 241000, China

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Figures & Tables(6)

Fig. 1. Inpainting effect of global search and dynamic range search. (a) Original images; (b) global search; (c) dynamic range search

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Fig. 2. Inpainting time for global search and dynamic range search

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Fig. 3. Inpainting effects of different sizes. (a) Original images; (b) size 5×5; (c) size 7×7; (d) size 9×9; (e) size 11×11

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Fig. 4. Inpainting effects comparison between six different algorithms and the proposed algorithm. (a) Original images; (b) inpainting results by MD algorithm; (c) inpainting results by PDE algorithm; (d) inpainting results by NN algorithm; (e) inpainting results by Ref.[20] method; (f) inpainting results by Criminisi algorithm; (g) inpainting results by Ref.[3] method; (h) inpainting results by proposed algorithm

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Table 1. Inpainting effects comparison of evaluation index for different algorithms

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Table 1. Inpainting effects comparison of evaluation index for different algorithms

Image	Index	MDmethod	NNmethod	Method inRef.[20]	Criminisimethod	Method inRef.[3]	Proposedmethod
	PSNR /dB	29.5975	25.8096	24.3662	27.3331	27.6764	27.3669
Air	SSIM	0.9628	0.8668	0.7940	0.8684	0.8681	0.8675
	r	0.9708	0.9299	0.9018	0.9504	0.9543	0.9507
	PSNR /dB	15.4539	16.3219	14.4868	16.4791	16.9938	20.7359
Car	SSIM	0.3874	0.7054	0.3692	0.7041	0.7161	0.6427
	r	0.7858	0.8417	0.7587	0.8473	0.8565	0.9291
	PSNR /dB	18.9067	18.1455	17.8397	18.1682	18.5533	18.3531
Lenna	SSIM	0.8987	0.8912	0.8508	0.8919	0.8917	0.8953
	r	0.8131	0.7760	0.7543	0.7779	0.7974	0.7870
	PSNR /dB	23.6609	22.3550	21.8943	22.4453	23.3841	23.5420
Lincoln	SSIM	0.9806	0.9604	0.9554	0.9587	0.9800	0.9804
	r	0.9415	0.9207	0.9107	0.9227	0.9377	0.9399
	PSNR /dB	35.5345	45.4129	24.9755	49.2218	44.7734	44.6925
Pimple	SSIM	0.9979	0.9995	0.9102	0.9997	0.9982	0.9982
	r	0.9964	0.9996	0.9591	0.9998	0.9996	0.9996
	PSNR /dB	24.6307	25.6090	20.7125	26.7295	26.2762	26.9381
Average	SSIM	0.8455	0.8847	0.7759	0.8847	0.8908	0.8768
	r	0.9015	0.8936	0.8569	0.8997	0.9091	0.9213

Table 2. Comparison of running time of different algorithms unit: s

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Table 2. Comparison of running time of different algorithms unit: s

Image	Method in Ref.[20]	Criminisi method	Method in Ref.[3]	Proposed method
Air	41.61	523.47	465.41	376.29
Car	124.50	2341.95	1739.68	1520.38
Lena	126.83	44182	34005	32789
Lincoln	48.52	333.37	269.79	201.26
Pimple	10.068	17.90	17.52	17.48

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Fengsui Wang, Zhengnan Liu, Linjun Fu. An Improved Criminisi Image Inpainting Method Based on Information Entropy and Gradient Factor[J]. Laser & Optoelectronics Progress, 2020, 57(22): 221006

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Paper Information

Category: Image Processing

Received: Feb. 11, 2020

Accepted: Mar. 31, 2020

Published Online: Oct. 24, 2020

The Author Email: Fengsui Wang (fswang@ahpu.edu.cn)

DOI:10.3788/LOP57.221006

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology