Fog Image Enhancement Algorithm Based on Boundary-Limited Weighte Least Squares Filtering

Hongyun Li; Lijun Yun; Yin Gao

doi:10.3788/CJL201946.0309002

Journals >Chinese Journal of Lasers >Volume 46 >Issue 3 >Page 0309002 > Article

Chinese Journal of Lasers
Vol. 46, Issue 3, 0309002 (2019)

Fog Image Enhancement Algorithm Based on Boundary-Limited Weighte Least Squares Filtering

Hongyun Li^1、*, Lijun Yun^2、*, and Yin Gao³

Author Affiliations

¹ Quanzhou Institute of Technology, Jinjiang, Fujian 362200, China

² College of Information, Yunnan Normal University, Kunming, Yunnan 650500, China

³ Quanzhou Institute of Equipment Manufacturing, Chinese Academy of Sciences, Jinjiang, Fujian 362200, China

show less

DOI: 10.3788/CJL201946.0309002 Cite this Article Set citation alerts

Hongyun Li, Lijun Yun, Yin Gao. Fog Image Enhancement Algorithm Based on Boundary-Limited Weighte Least Squares Filtering[J]. Chinese Journal of Lasers, 2019, 46(3): 0309002 Copy Citation Text

show less

Fig. 1. Flow chart of algorithm

Download full size

Fig. 2. Scattering cube

Download full size

Fig. 3. Comparison of transmission images. (a) Original image; (b) dark channel image in Ref.[8]; (c) transmission image in Ref.[8]; (d) dehazing image in Ref.[8]; (e) boundary constraint image in Ref.[14]; (f) transmission image in Ref.[14]; (g) dehazing image in Ref.[14]; (h) boundary constraint image by proposed algorithm; (i) optimized transmission image by proposed algorithm; (j) dehazing image by proposed algorithm

Download full size

Fig. 4. Qualitative comparison of results of different dehazing methods. (a) Original image; (b) Ref.[8]; (c) Ref.[14]; (d) Ref.[16]; (e) Ref.[17]; (f) Ref.[18]; (g) proposed algorithm

Download full size

Fig. 5. Qualitative comparison of sky region and detail features of different dehazing methods. (a) Original image; (b) Ref.[8]; (c) Ref.[14]; (d) Ref.[16]; (e) Ref.[17]; (f) Ref.[18]; (g) proposed algorithm

Download full size

Fig. 4	Method	e	Ψ	$\begin{matrix} \bar{r} \end{matrix}$	e+ $\begin{matrix} \bar{r} \end{matrix}$
	Ref.[8]	0.12	0	1.47	1.59
	Ref.[14]	0.21	0.15	2.62	2.83
Building	Ref.[16]	0.05	0	0.94	0.99
	Ref.[17]	0.04	0	1.11	1.15
	Ref.[18]	0.13	0	1.74	1.87
	Proposed	0.11	0	1.72	1.83
	Ref.[8]	0.02	0	0.92	0.94
	Ref.[14]	0.05	0	1.66	1.71
Mountain	Ref.[16]	0.01	0	0.89	0.9
	Ref.[17]	0.02	0.23	1.29	1.31
	Ref.[18]	0.02	0.09	1.23	1.25
	Proposed	0.03	0	1.5	1.53
	Ref.[8]	0.02	0	0.95	0.97
	Ref.[14]	0.11	0.31	2.62	2.73
Monitoringstation	Ref.[16]	0.04	0	1.1	1.14
	Ref.[17]	0.03	0	1.33	1.36
	Ref.[18]	0.07	0	1.93	2.00
	Proposed	0.03	0	1.57	1.6
	Ref.[8]	0.01	0.05	1.2	1.21
	Ref.[14]	0.01	0.05	1.59	1.6
Market	Ref.[16]	0.01	0.95	1.07	1.08
	Ref.[17]	0.01	0.97	1.53	1.54
	Ref.[18]	0	0.13	1.64	1.64
	Proposed	0.02	0.16	1.97	1.99

Table 1. Image quality evaluation

Hongyun Li, Lijun Yun, Yin Gao. Fog Image Enhancement Algorithm Based on Boundary-Limited Weighte Least Squares Filtering[J]. Chinese Journal of Lasers, 2019, 46(3): 0309002

Download Citation

Set citation alerts for the article

Tools

Set citation alerts for the article

Save the article for my favorites

Paper Information