计算机工程与应用2016，Vol.52Issue(1)：178-184,7.DOI:10.3778/j.issn.1002-8331.1501-0122
基于改进暗原色先验模型的快速图像去雾方法
Fast image de-hazing method based on improved dark channel prior model
摘要
Abstract
To deal with the image degradation problem induced by the haze or fog, a fast image de-hazing algorithm based on an improved dark channel prior model and tolerance mechanism is proposed. The atmosphere light is firstly estimated using dark channels, and then for calculating accurately the transmission map of the image with different scene depths, the dark channel prior model is improved by combining the interpolation and the minimum-maximum estimation methods, finally the de-hazing image is restored using the tolerance mechanism and atmospheric scatting model. The experimental results illustrate that, comparing with the original de-hazing methods based on dark channel prior, the proposed algorithm is very fast with a computation time reduced to 1/30 and effective for fog removal in both dark and light image areas. The improved dark channel prior model by combining interpolation and minimum-maximum estimation methods has a potential for real-time and robust image de-hazing.关键词
快速图像去雾/改进暗原色模型/容差机制/插值算法/最大最小估计法Key words
fast image de-hazing/improved dark channel prior model/tolerance mechanism/interpolation/minimum-maximum estimation分类
信息技术与安全科学引用本文复制引用
杜宏博,王丽会..基于改进暗原色先验模型的快速图像去雾方法[J].计算机工程与应用,2016,52(1):178-184,7.基金项目
贵州省教育厅自然科学基金青年项目(No.20090125) （No.20090125）
贵州大学人才引进科研项目(No.201333). （No.201333）
