结合改进Retinex及自适应分数阶微分的雾霾公路交通图像增强  

Haze traffic image enhancement based on improved retinex and adaptive fractional differential

作　　者：王卫星[1] 赵恒 WANG Wei-xing;ZHAO Heng(School of Information Engineering, Chang′an University, Xi′ an 710064, China)

机构地区：[1]长安大学信息工程学院,陕西西安710064

出　　处：《光学精密工程》2020年第8期1820-1834,共15页Optics and Precision Engineering

基　　金：国家自然科学基金资助项目(No.61170147,No.1972060)。

摘　　要：为了提高雾霾天气条件下交通图像的对比度,清晰度和颜色保真度,减少图像退化所带来的负面影响,提出了一种采用快速引导滤波平滑约束的Retinex及自适应分数阶微分的雾霾天气交通图像增强算法。首先,该方法将原图像从RGB转换到YCbCr颜色空间,提取亮度分量构建初始图像;其次,构建变分模型,借助快速引导滤波构造目标函数的平滑约束项来准确估计初始照射分量;然后,使用Retinex模型获得初始反射分量,再采用自适应分数阶微分掩膜对初始反射分量进行增强得到亮度分量的增强结果,该方法在图像噪声抑制和细节增强方面性能良好;最后,将处理后的反射分量结合Cb,Cr色差信息从YCbCr转换到RGB颜色空间即得到最终增强图像。本文对不同的雾霾交通图像进行了对比实验,实验结果表明,新方法的标准差(STD)和平均梯度(AG)较原图至少提高1.12倍和4倍以上,信息熵(E)至少提高4.76%以上,综合性能优于其他的对比算法。新方法在图像增强和细节保持方面得到了很好地改进,有效地提高了雾霾天气条件下公路交通图像的颜色保真度、对比度和细节清晰度等,使得增强后的图像视觉效果和可视度明显改善,更加真实自然。To improve the contrast,clarity,and color fidelity of the traffic image in haze weather and reduce the negative impact of image degradation,a haze traffic image enhancement algorithm based on fast-guided filtering smoothing constraint for Retinex and adaptive fractional differential was proposed herein.First,an original image was converted from RGB space to YCbCr space,and the brightness component Y was extracted to construct the initial image.Second,a variational model was constructed,and the fast-guided filter was used to construct the smoothing constraints of the objective function to accurately estimate the initial irradiation component.Then,the Retinex model was used to obtain the initial reflection component,and the adaptive fractional differential mask was applied to enhance in order to obtain,which was the enhancement result of the Y component.The method showed good performance in terms of image noise suppression and detail enhancement.Finally,the reflection component was converted from YCbCr to RGB space by combining with the color difference information of Cb and Cr,to obtain the final enhanced image.In this study,the contrast experiments of different haze traffic images were tested.The experimental results indicate that the standard deviationand average gradient of the new method are at least 1.12 times and 4 times higher than those of the original image,and the information entropyis at least 4.76%higher.The comprehensive performance of the proposed method is better than that of other comparison algorithms.Thus,the method is satisfactory for image enhancement and detail retention.It effectively improves the color fidelity,intensity contrast,and texture clarity forroad traffic images in haze weather.Moreover,it makes the image more visible,and the color more natural.

关 键 词：快速引导滤波 RETINEX 自适应分数阶微分 图像增强 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]