面向复杂雪天场景的单幅图像去雪方法

周刚; 任静旭; 刘邱铃; 陈娟; 贾振红

doi:10.13568/j.cnki.651094.651316.2023.08.27.0001

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面向复杂雪天场景的单幅图像去雪方法

信息科学与技术 | 更新时间：2026-01-21

- 面向复杂雪天场景的单幅图像去雪方法
- 面向复杂雪天场景的单幅图像去雪方法
- 新疆大学学报（自然科学版中英文） 2024年41卷第3期页码：310-318
- 作者机构：
  
  新疆大学计算机科学与技术学院信号检测与处理重点实验室
- 作者简介：
- 基金信息：
  
  国家自然科学基金“面向特殊天气的场景文本检测方法研究”（62166040）;新疆维吾尔自治区自然科学基金“面向沙尘天气的目标检测方法研究”（2021D01C057）
- DOI：10.13568/j.cnki.651094.651316.2023.08.27.0001
  中图分类号： TP391.41
- 纸质出版：2024
- 稿件说明：
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[1]周刚,任静旭,刘邱铃,等.面向复杂雪天场景的单幅图像去雪方法[J].新疆大学学报(自然科学版)(中英文),2024,41(03):310-318.
[1]周刚,任静旭,刘邱铃,等.面向复杂雪天场景的单幅图像去雪方法[J].新疆大学学报(自然科学版)(中英文),2024,41(03):310-318. DOI： 10.13568/j.cnki.651094.651316.2023.08.27.0001.

DOI：10.13568/j.cnki.651094.651316.2023.08.27.0001.

摘要

降雪是一种复杂的天气现象，雪花多尺度、运动轨迹复杂以及远景呈现雾天效果．然而现有的单幅图像去雪方法以及数据集，并没有考虑到这些复杂的情况，从而限制了去雪方法在真实雪天图像上的表现．基于此，首先根据图像的深度信息构造了一种联合雪花和雾的雪天成像模型，合成了具有真实感的雪天图像数据集．然后设计了一种端到端的图像恢复网络，将去雾模块和去雪模块级联，并进行联合训练．其中去雪模块采用了双层U型网络用于解决雪花多尺度和轨迹复杂的问题．最后将该方法同其它最先进的方法进行实验对比，证明该方法在合成数据集和真实图像中都具有非常好的效果，且能够提升后续高级视觉任务性能．

Abstract

Snowfall is a complex weather phenomenon that involves multiple scales of snowflakes

complex motion trajectories

and a foggy effect in the long term. However

existing single image snow removal methods and datasets do not take into account these physical properties

which limits the performance of snow removal methods on real snowfall images. To address this issue

we first constructed a snow imaging model that combines snowflakes and fog based on the depth information of the image

and produced a realistic synthetic snowfall image dataset. Then

we designed an end-to-end image restoration network that cascades the defogging and snow removal modules for joint training. The snow removal module adopts a double U-shaped network to solve the problem of multi-scale snowflakes and multi-directional trajectories. Finally

the experimental comparison between our method and other state-of-art methods proves that our method has very good performance in both synthetic datasets and real images

and benefits subsequent visual tasks.

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Keywords

references

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