Searching Method for Optimal Code Sequence of Coded Exposure Based on Memetic Algorithm

Guangmang Cui; Kuaikuai Yu; Xiaojie Ye; Jufeng Zhao; Liyao Zhu

doi:10.3788/AOS201939.0311004

Journals >Acta Optica Sinica >Volume 39 >Issue 3 >Page 0311004 > Article

Acta Optica Sinica
Vol. 39, Issue 3, 0311004 (2019)

Searching Method for Optimal Code Sequence of Coded Exposure Based on Memetic Algorithm

Guangmang Cui^1、2, Kuaikuai Yu^2、*, Xiaojie Ye¹, Jufeng Zhao¹, and Liyao Zhu¹

Author Affiliations

¹ School of Electronics and Information, Hangzhou Dianzi University, Hangzhou, Zhejiang 310018, China

² Science and Technology on Electro-Optical Information Security Control Laboratory, Tianjin 300308, China

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DOI: 10.3788/AOS201939.0311004 Cite this Article Set citation alerts

Guangmang Cui, Kuaikuai Yu, Xiaojie Ye, Jufeng Zhao, Liyao Zhu. Searching Method for Optimal Code Sequence of Coded Exposure Based on Memetic Algorithm[J]. Acta Optica Sinica, 2019, 39(3): 0311004 Copy Citation Text

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Fig. 1. Traditional exposure mode. (a) Imaging exposure model; (b) Fourier transform amplitude curve

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Fig. 2. Coded exposure mode. (a) Coded exposure imaging model; (b) Fourier transform amplitude curve

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Fig. 3. Searching method for optimal code sequence of coded exposure based on Memetic algorithm

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Fig. 4. Comparison of frequency amplitude curves for code sequence of 32 bits

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Fig. 5. Comparison of frequency amplitude curves for code sequence of 52 bits

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Fig. 6. Comparison of frequency amplitude curves for code sequence of 112 bits

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Fig. 7. Simulated blurred images and deblurring results for image “Target” with code sequence of 32 bits. (a) Traditional exposure mode; (b) coded exposure mode plus genetic search method; (c) coded exposure mode plus Memetic searching method

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Fig. 8. Simulated blurred images and deblurring results for image “Target” with code sequence of 32 bits. (a) Traditional exposure mode; (b) coded exposure mode plus genetic search method; (c) coded exposure mode plus Memetic searching method

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Fig. 9. Simulated blurred images and deblurring results for image “Cameraman” with code sequence of 32 bits. (a)Traditional exposure mode; (b) coded exposure mode plus genetic search method; (c) coded exposure mode plus Memetic searching method

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Fig. 10. Simulated blurred images and deblurring results for image “Cameraman” with code sequence of 52 bits. (a) Traditional exposure mode; (b) coded exposure mode plus genetic search method; (c) coded exposure mode plus Memetic searching method

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Code sequence length	Evaluate index	Genetic search method	Proposed method
32	MIN	0.26	0.85
	VAR	6.07	3.62
52	MIN	0.35	0.46
	VAR	9.17	5.39
112	MIN	0.39	0.44
	VAR	24.72	19.55

Table 1. Objective evaluation results of frequency amplitude curves for code sequence

Code sequence length	Exhaustion method	Genetic search method	Proposed method
32	~1.491´10⁵	4.035	3.862
52	~1.262´10¹¹	7.264	5.678
112	~1.455´10²⁹	22.043	14.768

Table 2. Execution time of searching methods for optimal code sequences

Code sequence length	PSF length	Evaluateindex	Traditional exposure method	Coded exposure by genetic search method	Coded exposure by proposed method
32	7	SNR	15.4310	27.6651	36.6306
		SSIM	0.8352	0.9779	0.9914
52	11	SNR	14.6065	31.6558	36.4372
		SSIM	0.8083	0.9852	0.9904

Table 3. Objective evaluation results of simulated deblurring images for image “Target”

Code sequence length	PSF length	Evaluateindex	Traditional exposure method	Coded exposure by genetic search method	Coded exposure by proposed method
32	7	SNR	10.4900	29.5233	32.5042
		SSIM	0.2475	0.9376	0.9633
52	11	SNR	7.8144	27.4262	32.2805
		SSIM	0.1547	0.9245	0.9621

Table 4. Objective evaluation results of simulated deblurring images for image “Cameraman”

Guangmang Cui, Kuaikuai Yu, Xiaojie Ye, Jufeng Zhao, Liyao Zhu. Searching Method for Optimal Code Sequence of Coded Exposure Based on Memetic Algorithm[J]. Acta Optica Sinica, 2019, 39(3): 0311004

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