Fast Defogging Algorithm Based on Adaptive Exponentially Weighted Moving Average Filtering

Kang Mei; Xiaoqin Liu; Chao Mu; Xiaoqi Qin

doi:10.3788/CJL202047.0109001

Chinese Journal of Lasers, Volume. 47, Issue 1, 0109001(2020)

Fast Defogging Algorithm Based on Adaptive Exponentially Weighted Moving Average Filtering

Kang Mei^1,2、**, Xiaoqin Liu^1、*, Chao Mu¹, and Xiaoqi Qin^1,2

¹Key Laboratory of Atmospheric Optics, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei, Anhui 230031, China

²University of Science and Technology of China, Hefei, Anhui 230026, China

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Figures & Tables(11)

Fig. 1. EWMA algorithm. (a) β=0; (b) β=0.35; (c) β=0.65; (d) β=0.95

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Fig. 2. AEWMA algorithm. (a) σ=1; (b) σ=5; (c) σ=15; (d) σ=30

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Fig. 3. Comparison of different filters. (a) Noise image; (b) bilateral filter; (c) WLS filter; (d) AEWMA filter

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Fig. 4. Image defogging process based on dark channel prior. (a) Fog image; (b) dark-channel image; (c) defogged image

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Fig. 5. Comparison of improved dark-channel images under different parameters. (a)-(c) Results obtained when r=3 and K=15, 35, and 65, respectively; (d)-(f) results obtained when r=5 and K=15, 35, and 65, respectively; (g)-(i) results obtained when r=7 and K=15, 35, and 65, respectively

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Fig. 6. Atmospheric light estimation. (a) Kim's algorithm; (b) Su Chang's algorithm

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Fig. 7. Images of transmittance distributions. (a) Coarse transmittance; (b) optimized transmittance

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Fig. 8. Comparison of results of four-group experiments. (a) Original image; (b) Tarel algorithm; (c) bilateral filtering algorithm; (d) guide filtering algorithm; (e) proposed algorithm

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Table 1. Comparison of indexes of different filters
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Table 1. Comparison of indexes of different filters
Image (size: 512 pixel×521 pixel) Noise image Bilateral filtered image WLS filtered image AEWMA filtered image
PSNR /dB 26.9876 32.6219 31.9278 32.4909
Time /s 3.86340 0.79045 0.08148

Table 2. Comparison of time consumption of different defogging algorithmss
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Table 2. Comparison of time consumption of different defogging algorithmss
Image size /pixel Tarel algorithm Bilateral filtering algorithm Guide filtering algorithm Proposed algorithm
440×440 1.3390 2.4920 0.4512 0.2010
600×400 1.5830 3.1510 0.5723 0.2480

Table 3. Objective evaluation of defogged image quality

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Table 3. Objective evaluation of defogged image quality

Image	Defogging algorithm	Detail performance	Color performance	Structure information
The first row,the first column (Fig. 8)	Tarel algorithm	0.3693	0.5383	0.7327
	Bilateral filtering algorithm	0.3699	0.5546	0.7755
	Guide filtering algorithm	0.3402	0.5089	0.7903
	This paper's algorithm	0.3854	0.5564	0.7637
The second row,the first column(Fig. 8)	Tarel algorithm	0.2599	0.6699	0.8012
	Bilateral filtering algorithm	0.4843	0.5759	0.6634
	Guide filtering algorithm	0.4262	0.5506	0.7288
	This paper's algorithm	0.5250	0.8001	0.7873

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Kang Mei, Xiaoqin Liu, Chao Mu, Xiaoqi Qin. Fast Defogging Algorithm Based on Adaptive Exponentially Weighted Moving Average Filtering[J]. Chinese Journal of Lasers, 2020, 47(1): 0109001

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