吉林大学学报(理学版) ›› 2024, Vol. 62 ›› Issue (5): 1138-1144.

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 基于高低频特征增强和透射率修正的复杂图像去雾方法

王士斌, 郭嘉懿   

  1. 河南师范大学 计算机与信息工程学院, 河南 新乡 453000
  • 收稿日期:2024-01-25 出版日期:2024-09-26 发布日期:2024-09-26
  • 通讯作者: 王士斌 E-mail:19838936533@163.com

Defogging Method of Complex Images Based on  High and Low Frequency Feature Enhancement and Transmittance Correction

WANG Shibin, GUO Jiayi   

  1. College of Computer and Information Engineering, Henan Normal University, Xinxiang 453000, Henan Province, China
  • Received:2024-01-25 Online:2024-09-26 Published:2024-09-26

摘要: 针对复杂图像中存在非均匀散射介质(如大气湍流、 烟雾、 雾霾等), 导致光线在不同区域的传播和散射特性不同, 较难准确恢复图像能见度的问题, 提出一种基于高低频特征增强和透射率修正的复杂图像去雾方法. 首先, 基于奇异值分解和Gamma拐点校正, 设计低频特征增强方法; 其次, 基于Shearlet变换分解和非线性变换, 得到高频特征增强方法; 再次, 利用软抠图精化所估计的透射率, 构建透射率修正策略; 最后, 融合上述3种方法, 根据大气光值和精化透射率, 完成图像去雾, 分别增强高、 低频特征后, 将两者叠加, 获得增强的去雾图像. 经去雾图像的视觉感观和客观评价指标结果验证表明, 该方法的去雾效果较好, 能有效恢复复杂图像的细节信息, 改善图像的整体视觉质量.

关键词: 低频特征增强, 高频特征增强, 透射率估计, 透射率精化, 复杂图像去雾

Abstract: Aiming at the problem that there were non-uniform scattering media  (such as atmospheric turbulence, smoke, haze, etc.) incomplex images, which led to different propagation and scattering characteristics of light in different regions, making it difficult to accurately restore the visibility of the image, we proposed a defogging method of  complex image based on  high and low frequency feature enhancement and transmittance correction. Firstly, we designed low frequency feature enhancement methods 
based on singular value decomposition and Gamma inflection point correction. Secondly, based on Shearlet transformation decomposition and nonlinear transformation, we obtained a high frequency feature enhancement method. Thirdly, we used soft cutout to refine the estimated transmittance and constructed a transmittance correction strategy. Finally, by integrating the above three methods, based on atmospheric light values and refined transmittance, image dehazing was completed. After enhancing high and low frequency features respectively, we superimposed  the two  to obtain an enhanced dehazing image. The visual perception and objective evaluation indicators  of dehazing images have been  verified that the proposed method has good dehazing effect and  can effectively restore the detailed information of complex images,  improving the overall visual quality of the images.

Key words: low frequency feature enhancement, high frequency feature enhancement, estimation of transmittance, refinement of transmittance, defogging of complex image

中图分类号: 

  • TP391