改进的基于雾气理论的视频去雾

为了进一步提高有雾视频的可用性,提出了一种改进的基于雾气理论的视频去雾方法。该方法以雾气理论为基础,利用暗原色先验知识以及Retinex方法和图像融合的方式,将从视频背景图像求取的大气光值和介质传播图应用于视频的所有帧以便去除雾气。从主观定性评价、客观定量评价和运算速度3个方面对视频去雾效果进行了评价。结果表明,对分辨率为480×640的视频,本文方法的运算速度为5.45frame/s,不仅获得了较快的处理速度且能有效避免复原视频中出现颜色跳变的现象。由于本文采用区间估计的方式对大气光值进行估计,同时利用图像复原和图像增强的方法求取介质传播图,因此,复原视频的清晰度和对比度比典型的视频去雾方法有所提高,颜色效果也比较好。

Improved video defogging based on fog theory

To improve the usability of a foggy video, an improved video defogging method based on fog theory was proposed. By using dark channel prior knowledge, Retinex method and image fusion, the method applies the values of global atmospheric light and a medium transmission map estimated from the video backgrfound image to defogging of all the video frames. The effects of the defogging for the video image were evaluated by three methods in subjective qualitative evaluation, objective quantitative evaluation and operation speeds. Experimental results demonstrate that the proposed method runs at 5.45 frame/s for a video image of 480×640, and it not only obtains a fast processing speed but also effectively avoids color jump during the process of restoring image. As the modified method uses the interval estimation to estimate the value of global atmospheric light, and combinates image restoration and image enhancement to obtain the value of medium transmission map, it improves the visibility and contrast of restored video image effectively as well as color effect as compared with the traditional video defogging methods.