摘要
由于煤矿井下环境恶劣,存在大量的粉尘、水雾,使得煤矿井下视频监控获取的图像严重降质,而现有的基于暗通道先验的尘雾清晰化算法在处理煤矿尘雾图像时存在局限性,因此提出了一种改进的基于负片修正的尘雾图像清晰化算法。针对原有算法产生的严重的光环效应,通过建立参数间的映射实现了修正参数的精细化,从而有效的抑制了光环效应的产生。考虑获取的复原图像亮度比较低,对其进行伽马校正并获得最终清晰化图像。与其他算法相比,该算法能够有效的对尘雾图像进行清晰化复原,使得复原图像色彩更加饱和、信息量更加丰富,展现了该算法的优越性。
Due to the poor underground environment, there is a lot of dust and mist, which makes the images of underground video in coal mines seriously degraded. Concerning that the existing transcendental dust and mist clearness algorithm based on dark channel has limitation in dealing with dust and mist degraded images, we propose a kind of restoration algorithm for dust and mist degraded images based on improved negative colreetion. For the serious halo effect of original algorithm, we establish the mapping among the parameters to achieve the correction parameters refinement. Considering that the brightness of restored images is relatively low, Gama correction is adopted to get final clear images. The experiment results show that the proposed algorithm can effectively achieve the restoration of dust and mist degraded images, and the restored images have more saturated colors, richer information compared with other algorithms, which demonstrates the superiority of the proposed algorithm.
出处
《煤矿安全》
北大核心
2017年第9期116-119,共4页
Safety in Coal Mines
基金
国家重点研发计划重点专项资助项目(2016YFC0801807
2016YFC0801805)
关键词
煤矿图像
负片修正
尘雾清晰化
光环效应
去雾
mine image
negative correction
restoration of dust and mist degraded image
halo effect
defogging
