伽马校正
亮度
像素
人工智能
计算机视觉
计算机科学
对比度增强
对比度(视觉)
图像(数学)
图像对比度
光学
物理
失真(音乐)
数学
图像增强
电信
医学
放射科
磁共振成像
放大器
带宽(计算)
作者
Gang Cao,Lihui Huang,Huawei Tian,Xianglin Huang,Yongbin Wang,Ruicong Zhi
标识
DOI:10.1016/j.compeleceng.2017.09.012
摘要
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.
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