基于补偿透射率和自适应雾浓度系数的图像复原算法

doi:10.11959/j.issn.1000-436x.2020009

Abstract

Abstract:

Aiming at the drawbacks of traditional dark channel prior,which was prone to distortion and Halo effects in the bright areas,a haze image restoration algorithm based on compensated transmission and adaptive haze concentration coefficient was proposed.First of all,a Gaussian function was used to fit the attenuation relationship between the haze and haze-free image,and the compensation transmission was set to correct the initial transmission.Then the characteristics of haze was analyzed,the concept of brightness entropy was introduced and the bright channel operation was performed to acquire entropy value with pixel by pixel.Combined with the Gaussian pyramid to extract texture features,the haze distribution map was obtained.An adaptive transformation was established to seek the haze concentration coefficient and get the accurate transmission.Finally,the recovery results were restored by improved atmospheric light value and atmospheric scattering model.Experimental results show that the recovered image has better color and detail,the degree of dehazing is thorough,the brightness is appropriate,and the effect is clear and natural.

Key words: image restoration, dehazing, dark channel prior, transmission, atmospheric scattering model

CLC Number:

TP391.41

Yan YANG,Zhiwei WANG. Image restoration algorithm based on compensated transmission and adaptive haze concentration coefficient[J]. Journal on Communications, 2020, 41(1): 66-75.

Figures/Tables 15

References 19

[1]	AL-SAMMARAIE M F , . Contrast enhancement of roads images with foggy scenes based on histogram equalization[C]// International Conference on Computer Science ＆ Education(ICCSE). 2015: 95-101.
[2]	YAO L , LIN Y , MUHAMMAD S . An improved multi-scale image enhancement method based on retinex theory[J]. Journal of Medical Imaging ＆ Health Informatics, 2018,8(1): 122-126.
[3]	TAN R , . Visibility in bad weather from a single image[C]// IEEE Conference on Computer Vision and Pattern Recognition(CVPR). 2008: 1-8.
[4]	HE K M , JIAN S , TANG X O . Single image haze removal using dark channel prior[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011,33(12): 2341-2353.
[5]	ZHU Q S , MAI J M , SHAO L . A fast single image haze removal algorithm using color attenuation prior[J]. IEEE Transactions on Image Processing, 2015,24(11): 3522-3533.
[6]	MENG G F , WANG Y , DUAN J Y ,et al. Efficient image dehazing with boundary constraint and contextual regularization[C]// The IEEE International Conference on Computer Vision (ICCV). 2013: 617-624.
[7]	CAI B L , XU X M , JIA K ,et al. DehazeNet:an end-to-end system for single image haze removal[J]. IEEE Transactions on Image Processing, 2016,25(11): 5187-5198.
[8]	REN W Q , LIU S , ZHANG H ,et al. Single image dehazing via multi-scale convolutional neural networks[C]// European Conference on Computer Vision (ECCV), 2016: 154-169.
[9]	LIU R , FAN X , HOU M ,et al. Learning aggregated transmission propagation networks for haze removal and beyond[J]. IEEE Transactions on Neural Networks and Learning Systems, 2019,30(10): 2973-2986.
[10]	杨燕, 陈高科 . 基于光补偿和逐像素透射率的图像复原算法[J]. 通信学报, 2017,38(5): 48-56.
	YANG Y , CHEN G K . Single image visibility restoration using optical compensation and pixel-by-pixel transmission estimation[J]. Journal on Communications, 2017,38(5): 48-56.
[11]	郭璠, 唐琎, 蔡自兴 . 基于融合策略的单幅图像去雾算法[J]. 通信学报, 2014,35(7): 199-207.
	GUO F , TANG J , CAI Z X . Single image defogging based on fusion strategy[J]. Journal on Communications, 2014,35(7): 199-207.
[12]	HE K M , SUN J , TANG X O . Guided image filtering[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013,35(6): 1397-1409.
[13]	YU T , RIAZ I , PIAO J C ,et al. Real-time single image dehazing using block-to-pixel interpolation and adaptive dark channel prior[J]. IET Image Processing, 2015,9(9): 725-734.
[14]	LI S T , HAO Q B , KANG X D ,et al. Gaussian pyramid based multiscale feature fusion for hyperspectral image classification[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018,11(9): 3312-3324.
[15]	SUN W , WANG H , SUN C ,et al. Fast single image haze removal via local atmospheric light veil estimation[J]. Computers ＆ Electrical Engineering, 2015,46(C): 371-378.
[16]	ANCUTI C , ANCUTI C O , VLEESCHOUWER C D . D-HAZY:a dataset to evaluate quantitatively dehazing algorithms[C]// IEEE International Conference on Image Processing(ICIP). 2016: 2226-2230.
[17]	HAUTIERE N , TAREL J P , Aubert D ,et al. Blind contrast enhancement assessment by gradient ratioing at visible edges[J]. Image Analysis ＆ Stereology, 2011,27(2): 87-95.
[18]	杨红, 崔艳 . 基于开运算暗通道和优化边界约束的图像去雾算法[J]. 光子学报, 2018,47(6): 244-250.
	YANG H , CUI Y . Image defogging algorithm based on opening dark channel and improved boundary constraint[J]. Acta Photonica Sinica, 2018,47(6): 244-250.
[19]	杨燕, 陈高科, 周杰 . 基于高斯权重衰减的迭代优化去雾算法[J]. 自动化学报, 2019,45(4): 819-828.
	YANG Y , CHEN G K , ZHOU J . Iterative optimization defogging algorithm using gaussian weight decay[J]. Acta Automatica Sinica, 2019,45(4): 819-828.

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图像	He算法		Meng算法		Ren算法		Liu算法		本文算法
图像	P	r	p	r	p	r	p	r	p	r
图像1	8.349	1.714	5.377	2.541	17.654	1.523	19.794	1.507	18.581	1.663
图像2	13.114	1.769	22.514	2.659	9.112	1.493	10.891	1.645	20.812	2.014
图像3	6.437	1.375	12.561	1.114	11.117	1.281	15.594	1.681	16.185	1.579
图像4	25.881	1.709	30.019	1.850	18.647	1.349	30.113	2.593	29.011	2.453
图像5	3.745	1.416	3.129	1.569	5.641	1.133	5.634	1.363	6.132	1.647
图像6	8.231	1.715	11.154	1.921	12.858	1.309	13.864	1.609	13.041	2.181
均值	10.959	1.616	14.125	1.942	12.504	1.348	15.981	1.733	17.293	1.922

图像	He算法		Meng算法		Ren算法		Liu算法		本文算法
图像	θ	t	θ	t	θ	t	θ	t	θ	t
图像1	0.000 21	2.59	0.003 75	3.14	0	2.54	0	2.46	0.000 01	2.67
图像2	0.000 33	2.18	0.000 59	3.18	0.006 99	2.16	0.006 42	2.08	0.000 01	2.15
图像3	0	2.14	0.000 03	4.43	0.001 14	2.65	0.001 03	2.75	0	2.41
图像4	0.000 28	2.57	0.000 04	3.49	0	4.12	0	3.98	0	2.23
图像5	0.001 59	2.78	0	4.41	0.011 34	3.79	0.010 14	3.54	0	2.28
图像6	0.001 13	2.64	0	4.40	0.015 73	4.04	0.011 24	3.76	0.000 16	2.19
均值	0.000 59	2.48	0.000 73	3.84	0.005 86	3.21	0.004 81	3.09	0.000 03	2.32

算法	SSIM	PSNR	运行时间/s
He算法	0.754	16.514	2.44
Meng算法	0.735	16.297	3.17
Ren算法	0.792	17.664	2.49
Liu算法	0.792	17.664	2.66
本文算法	0.761	17.671	2.32

Image restoration algorithm based on compensated transmission and adaptive haze concentration coefficient

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