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结合区域最小熵和邻域雾线优化的图像去雾

韩科磊 黄鹤 胡凯益 王会峰 高涛

北京大学学报(自然科学版)2025,Vol.61Issue(5):869-883,15.
北京大学学报(自然科学版)2025,Vol.61Issue(5):869-883,15.DOI:10.13209/j.0479-8023.2025.064

结合区域最小熵和邻域雾线优化的图像去雾

Dehazing Method Integrating Regional Minimum Entropy and Neighborhood Haze Line Optimization

韩科磊 1黄鹤 1胡凯益 1王会峰 2高涛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. 长安大学电子与控制工程学院,西安 710064
  • 3. 长安大学数据科学与人工智能研究院,西安 710064
  • 折叠

摘要

Abstract

An improved image dehazing method is proposed to address the issues of blurred details and color distortion in the restored image obtained by traditional dehazing algorithms.Firstly,the main structural image and the minimum channel image of the hazy image are acquired.The brightness mapping of the main structural image is calculated,and the maximum and sub-maximum points are identified to form four candidate regions.The median value of the region with the minimum entropy is selected as the global atmospheric light value.Subsequently,a fog line reliability evaluation parameter is introduced to determine whether transmission rate points belong to the noise area.Clustering of transmission rate points in the noise area is conducted,and the transmission rate is optimized using neighborhood fog lines.Clusters with too few pixels are merged,and the selection range of the maximum irradiance is appropriately expanded to compensate for errors caused by limited areas.Finally,edge information in the minimum channel is extracted using a side window box filter.An adaptive weight factor based on the characteristics of fog line clustering results is designed to remove texture information,further refine the transmission rate,and ultimately obtain the restored image based on the atmospheric imaging model.Experimental results demonstrate that the proposed algorithm shows significant performance improvements compared with various dehazing algorithms,with enhancements in information entropy,average gradient,blur coefficient,and fog concentration evaluation index(FADE),resulting in more complete details and better color matching with human visual perception in the restored image.

关键词

区域最小熵/相对总变分/雾霾线理论/图像处理/去雾

Key words

regional minimum entropy/relative total variation/haze line theory/image processing/defogging

引用本文复制引用

韩科磊,黄鹤,胡凯益,王会峰,高涛..结合区域最小熵和邻域雾线优化的图像去雾[J].北京大学学报(自然科学版),2025,61(5):869-883,15.

基金项目

国家自然科学基金(52572353)、陕西省重点研发计划(2024GX-YBXM-288)、陕西省留学人员科技活动择优资助项目(2023001)和中央高校基本科研业务费(300102325501)资助 (52572353)

北京大学学报(自然科学版)

OA北大核心

0479-8023

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