一种非线性变换的自适应透射率去雾算法

doi:10.19665/j.issn1001-2400.2022.01.022

西安电子科技大学学报 ›› 2022, Vol. 49 ›› Issue (1): 208-215.doi: 10.19665/j.issn1001-2400.2022.01.022

• 计算机科学与技术&人工智能 • 上一篇下一篇

一种非线性变换的自适应透射率去雾算法

孙景荣¹(),谢林昌¹(),杜梦欣¹(),罗丽燕^2,³()

1.西安电子科技大学空间科学与技术学院,陕西西安 710071
2.桂林电子科技大学信息与通信学院,广西壮族自治区桂林 541004
3.认知无线电与信息处理省部共建教育部重点实验室,广西壮族自治区桂林 541004

收稿日期:2021-01-12 出版日期:2022-02-20 发布日期:2022-04-27
作者简介:孙景荣(1975—),女,副教授,博士,E-mail: jrsun@xidian.edu.cn;|谢林昌(1994—),男,西安电子科技大学硕士研究生,E-mail: 942554457@qq.com;|杜梦欣(1998—),女,西安电子科技大学硕士研究生,E-mail: 1367359340@qq.com;|罗丽燕(1987—),女,副教授,博士,E-mail: 897284553@qq.com
基金资助:
国家自然科学基金面上项目(62071363);“认知无线电与信息处理”教育部重点实验室2019年开放基金(CRKL190203);山东省机器人与智能技术重点实验室资助(2021001)

Adaptive transmittance dehazing algorithm based on non-linear transformation

SUN Jingrong¹(),XIE Linchang¹(),DU Mengxin¹(),LUO Liyan^2,³()

1. School of Aerospace Science and Technology,Xidian University,Xi'an 710071,China
2. School of Information and Communication Engineering,Guilin University of Electronic Technology,Guilin 541004,China
3. Key Laboratory of Cognitive Radio and Information Processing of Ministry of Education, Guilin University of Electronic Technology,Guilin 541004,China

Received:2021-01-12 Online:2022-02-20 Published:2022-04-27

摘要/Abstract

摘要：

人工智能的飞速发展使得图像处理技术广泛应用于新一代智能交通系统中。但由于现有图像去雾算法在应用于智能交通中会存在透射率估计不足的现象,导致所复原图像在景深突变区域存在色偏、晕影、对比度低等问题,严重影响了户外采集系统的性能。因此,提出一种非线性变换的自适应透射率去雾算法。通过对数映射并结合自适应参数将暗通道中处于高灰度区域的强度值进行尺度压缩,获得原始无雾图像的暗通道,进而估计出初始透射率;根据像素亮度与饱和度的差值并引入调整因子,对天空区域透射率进行补偿,结合引导滤波,对补偿透射率进行平滑处理,获取自适应优化透射率,再由大气散射模型得到去雾后的图像。仿真结果表明,该算法对天空以及景深突变区域去雾效果清晰自然,纹理细节丰富,无明显伪影及色彩偏移,明亮适中;在平均梯度、信噪比、结构相似性、信息熵等参数方面都优于其他线性变换算法,各指标平均提高约6.4%,可有效地改善去雾图像在景深突变区域所存在的光晕以及失真现象。

关键词: 图像处理, 图像去雾, 衰减先验, 对数变换

Abstract:

The rapid development of artificial intelligence has made image processing technology widely used in the new generation of intelligent transportation systems.The issue of insufficient estimation of the transmission map when the existing image dehazed algorithms are applied to Intelligent Transportation Systems leads to the color shift,artifacts,and low contrast in the sudden depth of the field area for the restored images and seriously affects the performance of the outdoor acquisition system.Therefore,this paper proposes an adaptive transmittance defogging algorithm based on a nonlinear transformation.Through the use of logarithmic transformation and adaptive parameters,the intensity value of the high gray area in a dark channel is compressed that can obtain the dark channel of the original fog-free image.And then the initial transmittance is estimated.According to the difference between pixel brightness and saturation,an adjustment factor is introduced to compensate the transmittance of the sky area.After that,by combining with guided filtering,the compensated transmittance is smoothed to obtain the adaptive optimized transmittance.Then,on the basis of the atmospheric scattering model,the dehazed results are obtained.Simulation results show that the algorithm has a clear and natural dehazed effect on the sky and in the sudden depth of field area,with rich texture details,no obvious artifact and color shift,and moderate brightness.We conduct extensive experiments to report quantitative results for comparison,such as average gradient,signal-to-noise ratio,structural similarity,and information entropy.The parameters are better than those of other linear algorithms,and each index is improved by about 6.4% on average,which can effectively alleviate the halo and distortion of the dehazed image in the sudden depth of the field area.

Key words: image processing, image dehazing, attenuation prior, logarithmic transformation

中图分类号:

TP391.41

孙景荣,谢林昌,杜梦欣,罗丽燕. 一种非线性变换的自适应透射率去雾算法[J]. 西安电子科技大学学报, 2022, 49(1): 208-215.

SUN Jingrong,XIE Linchang,DU Mengxin,LUO Liyan. Adaptive transmittance dehazing algorithm based on non-linear transformation[J]. Journal of Xidian University, 2022, 49(1): 208-215.

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一种非线性变换的自适应透射率去雾算法

Adaptive transmittance dehazing algorithm based on non-linear transformation

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