Image haze removal using a hybrid of fuzzy inference system and weighted estimation

Jyun-Guo Wang; Shen-Chuan Tai; Cheng-Jian Lin

doi:10.1117/1.JEI.24.3.033027

23 June 2015 Image haze removal using a hybrid of fuzzy inference system and weighted estimation

Jyun-Guo Wang, Shen-Chuan Tai, Cheng-Jian Lin

Author Affiliations +

Journal of Electronic Imaging, Vol. 24, Issue 3, 033027 (June 2015). https://doi.org/10.1117/1.JEI.24.3.033027

Abstract

The attenuation of the light transmitted through air can reduce image quality when taking a photograph outdoors, especially in a hazy environment. Hazy images often lack sufficient information for image recognition systems to operate effectively. In order to solve the aforementioned problems, this study proposes a hybrid method combining fuzzy theory with weighted estimation for the removal of haze from images. A transmission map is first created based on fuzzy theory. According to the transmission map, the proposed method automatically finds the possible atmospheric lights and refines the atmospheric lights by mixing these candidates. Weighted estimation is then employed to generate a refined transmission map, which removes the halo artifact from around the sharp edges. Experimental results demonstrate the superiority of the proposed method over existing methods with regard to contrast, color depth, and the elimination of halo artifacts.

Citation Download Citation

Jyun-Guo Wang, Shen-Chuan Tai, and Cheng-Jian Lin "Image haze removal using a hybrid of fuzzy inference system and weighted estimation," Journal of Electronic Imaging 24(3), 033027 (23 June 2015). https://doi.org/10.1117/1.JEI.24.3.033027

Published: 23 June 2015

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available