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基于Pyramid-Kuwahara滤波器的航拍图像去雾方法

马天 黄鹤 李战一 杨澜 高涛 王会峰

南京大学学报(自然科学版)2024,Vol.60Issue(6):998-1008,11.
南京大学学报(自然科学版)2024,Vol.60Issue(6):998-1008,11.DOI:10.13232/j.cnki.jnju.2024.06.011

基于Pyramid-Kuwahara滤波器的航拍图像去雾方法

Aerial images defogging method based on Pyramid-Kuwahara filter

马天 1黄鹤 1李战一 1杨澜 2高涛 2王会峰3

作者信息

  • 1. 长安大学电子与控制工程学院,西安,710064||西安市智慧高速公路信息融合与控制重点实验室,西安,710064
  • 2. 长安大学信息工程学院,西安,710064
  • 3. 长安大学电子与控制工程学院,西安,710064
  • 折叠

摘要

Abstract

Aiming to address the challenges of the current UAV aerial image de-fogging method,including difficulties in considering de-fogging for different depths of field,excessive loss of edge details,and ineffective results,this paper proposes a de-fogging method based on the Pyramid-Kuwahara filter.Firstly,atmospheric light estimation and transmittance are solved using an improved dark channel prior method.Secondly,a multi-scale filter called Pyramid-Kuwahara is designed to optimize and extract atmospheric light details.Then,a method named MFRTV is proposed to enhance detail information in transmission based on the designed filter.Finally,the restored fog-free image is obtained by utilizing the atmospheric scattering model along with optimized transmittance and atmospheric light maps generated by the algorithm.Experimental results demonstrate that our proposed fog removal algorithm effectively restores image details in different depths of field while significantly reducing fog presence in experimental images.Moreover,it successfully removes fog even at further depths of field achieving in enhanced subjective visual effects and increased information richness compared to other control algorithms.The proposed algorithm exhibits significant improvements in parameters such as entropy,FADE(fog area density estimation),structural similarity index(SSIM),and average gradient.

关键词

图像去雾/滤波器/暗通道/RTV模型

Key words

image dehazed/filter/dark channel/RTV

分类

信息技术与安全科学

引用本文复制引用

马天,黄鹤,李战一,杨澜,高涛,王会峰..基于Pyramid-Kuwahara滤波器的航拍图像去雾方法[J].南京大学学报(自然科学版),2024,60(6):998-1008,11.

基金项目

国家自然科学基金(52172379),陕西省重点研发计划(2024GX-YBXM-288),中央高校基本科研业务费(300102324501),陕西省留学人员科技活动择优资助项目(2023001) (52172379)

南京大学学报(自然科学版)

OA北大核心CSTPCD

0469-5097

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