Dust Removal with Boundary and Spatial Constraint for Videos Captured in Car

B. Xiong, Zhiyong Huang, Shuangmei Peng, Xiang Fei, N. Shah
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Abstract

Videos captured in car often suffer from duston the wind screen glass. The dust particles on wind screendecrease the video quality and make them blur. Removingdust and restoring high quality dust-free video is a challengingtask in the field of video stream processing. In this paper, we propose an improved iterative optimization pipeline toremove dust from the videos. Our method employs boundaryconstraint to keep transmission map in a reasonable rangeand use spatial constraint on the transmission map to avoidintroduction of significant halo artifacts into the resultantvideo. With optimized transmission map as an initial condition, our method can separate dust layer and background layer frominput video frames and keeps the background frames beingcolor faithful with fine details. Test results demonstrate thatour proposed method can recover dust-free videos from thedust contaminated input videos and keep the resultant video color faithful.
基于边界和空间约束的车载视频除尘
在车内拍摄的视频经常会受到挡风玻璃上的灰尘的影响。风幕上的灰尘颗粒降低了视频质量,使视频模糊。在视频流处理领域,除尘和恢复高质量无尘视频是一项具有挑战性的任务。在本文中,我们提出了一种改进的迭代优化管道来去除视频中的灰尘。我们的方法采用边界约束使传输图保持在合理的范围内,并对传输图使用空间约束以避免在最终视频中引入明显的光晕伪影。该方法以优化后的传输图为初始条件,可以将灰尘层和背景层从视频帧中分离出来,并保持背景帧的颜色忠实,细节精细。测试结果表明,我们的方法可以从被灰尘污染的输入视频中恢复无尘视频,并保持最终视频颜色的忠实性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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