多媒体大数据时代一种有效的雾图像采集算法

Jinxing Niu, Hengcan Li
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引用次数: 0

摘要

多媒体大数据时代,户外图像经常受到大雾天气条件的影响,严重影响计算机视觉的应用。本文在大数据环境下提出了一种基于大数据分析的有效雾图像采集算法,并提出了基于直方图均衡化和暗通道先验方法的单幅图像去雾算法。需要用暗通道先验理论方法对雾图像的透射率和空气光进行估计,然后在除雾后接收到清晰的图像,并保持原有的颜色。实验结果表明,采用消雾暗通道先验方法处理后的图像能得到清晰的图像并保持原有的颜色,处理效果优于直方图均衡化方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An effective foggy image acquisition algorithm in multimedia big data era
Outdoor images are often degraded by fog weather conditions in the era of multimedia big data, which affect computer vision applications severely. In this paper, an effective fog image acquisition algorithm based on big data analysis is proposed in the big data environment, and single image defogging algorithm based on histogram equalisation and dark channel prior methods is proposed. The transmission and air light of the fog image need to be estimated by the dark channel prior theory methods, and then clear images can be received after defogging and keep the original colour. The experimental results show that the image by fog removal dark channel prior method can get clear images and keep the original colour, the treatment effect is better than that of the histogram equalisation method.
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