有效的多级梯度域过,用于图像和视频处理,具有增强的时间一致性
Neelam Kumari1, Isha Kansal1, Preeti Sharma2
1Chitkara University Institute of Engineering and Technology, Chitkara University.
Journal of visualized experiments : JoVE
|October 20, 2025
概括
本研究介绍了一种高效的多尺度梯度域过器,用于图像和视频 dehazing. 该方法提高了清晰度,减少了文物,改善了实时应用的视觉质量.
科学领域:
- 计算机视觉 计算机视觉
- 图像处理 图像处理
背景情况:
- 大气散射会降低图像清晰度,对计算机视觉任务构成挑战.
- 现有的排气方法往往具有高的计算成本,并且可能会丢失重要的梯度细节.
- 视频dehazing特别受到闪的文物的影响,限制了现实世界的应用.
研究的目的:
- 为图像和视频提出一种高效,高质量的除尘技术.
- 解决现有方法的局限性,包括计算成本,细节丢失和闪的文物.
- 为了增强纹理和边缘保留,同时保持视频dehazing中的时间连贯性.
主要方法:
- 建议使用多尺度梯度域加权引导图像过器 (GWGIF) 进行精细的传输地图估计.
- 最少保存子样本 (MPS) 用于高效的大气参数估计和复杂性降低.
- 引入了梯度相关系因子 (GCF),以减轻视频除尘中的闪文物.
主要成果:
- 拟议的方法实现了卓越的感知质量,PIQE,NIQE和BRISQE分数分别为26.98,2.78和20.18.
- 在视频解中,高时间连贯性被证明具有0.003.3的平均平方误差 (MSE) 偏差.
- 与现有方法相比,在视频脱雾中观察到闪的文物显著减少.
结论:
- 拟议的基于GWGIF的除尘技术为图像和视频处理提供了更高的效率和视觉质量.
- 该方法有效地保留了渐变细节,并改善了纹理/边缘保留.
- 由于其性能和时间稳定性,其适合于实时应用,如自动驾驶和监控等.
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