A robust haze-removal scheme in polarimetric dehazing imaging based on automatic identification of sky region. (December 2016)

• Record Type: Journal Article
• Authors: Zhang, Wenfei; Liang, Jian; Ju, Haijuan; Ren, Liyong; Qu, Enshi; Wu, Zhaoxin
• Is Part Of: Optics & laser technology. Volume 86(2016)
• Page Start: 145
• Page End: 151
• Publication Date: 2016-12
• Subjects: Imaging through turbid media -- Image enhancement -- Polarimetric imaging -- Visibility and imaging; Optics -- Periodicals; Lasers -- Periodicals; Electronic journals; 621.366
• DOI: 10.1016/j.optlastec.2016.07.015
• Languages: English
• ISSNs: 0030-3992

Abstract

Abstract: Quality enhancement of images acquired in hazy conditions is a significant research area in civil and military applications. The polarimetric dehazing methods have been exploited to dehaze hazy images and have proven to be effective in enhancing their quality. In this paper, by combining the polarimetric imaging technique and the dark channel prior technique, a robust haze-removal scheme is presented for the first time. On the one hand, the polarimetric imaging technique has advantages in recovering detailed information well, especially in dense hazy conditions; on the other hand, the dark channel prior technique provides a much more precise and convenient way to estimate the airlight radiance through extracting the sky region automatically. The experiments verify the practicability and effectiveness of the proposed dehazing scheme in quality enhancement of hazy images. Furthermore, comparison study demonstrates that the proposed scheme is superior to some sophisticated methods in terms of the visibility and contrast. We believe this scheme is beneficial in the image dehazing applications, especially for real-time applications. Highlights: A new haze-removal scheme is proposed based on the polarimetric imaging method. The sky region can be identified automatically from directly-snapped images. The DOP and AOP of airlight are estimated more accurate and fast. The new scheme outperforms the popular dehazing methods in quality enhancement.