Contrast enhancement of brightness-distorted images by improved adaptive gamma correction. (February 2018)

• Record Type: Journal Article
• Authors: Cao, Gang; Huang, Lihui; Tian, Huawei; Huang, Xianglin; Wang, Yongbin; Zhi, Ruicong
• Is Part Of: Computers & electrical engineering. Volume 66(2018)
• Page Start: 569
• Page End: 582
• Publication Date: 2018-02
• Subjects: Image enhancement -- Contrast enhancement -- Adaptive gamma correction -- Negative image -- CDF truncation -- Dimmed image -- Bright image; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2017.09.012
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: As an efficient image contrast enhancement (CE) tool, adaptive gamma correction (AGC) was previously proposed by relating gamma parameter with cumulative distribution function (CDF) of the pixel gray levels within an image. ACG deals well with most dimmed images, but fails for globally bright images and the dimmed images with local bright regions. However, such two categories of brightness-distorted images are universal in real scenarios, such as those incurred by improper exposure and white objects. In order to attenuate such deficiencies, in this paper we propose an improved AGC technique. The novel strategy of negative images is used to realize CE of the bright images, and the gamma correction modulated by truncated CDF is employed to enhance the dimmed ones. As such, local over-enhancement and structure distortion can be alleviated effectively. Extensive qualitative and quantitative experimental results show that our proposed method yields consistently good CE results.