基于亮度通道细节增强的低照度图像处理  

Low-Illuminance Image Processing Based on Brightness Channel Detail Enhancement

作　　者：蒋一纯 詹伟达[1] 朱德鹏[1] Jiang Yichun;Zhan Weida;Zhu Depeng(School of Electronic Information Engineering,Changchun University of Science and Technology,Changchun,Jilin 130022,China)

机构地区：[1]长春理工大学电子信息工程学院,吉林长春130022

出　　处：《激光与光电子学进展》2021年第4期83-91,共9页Laser & Optoelectronics Progress

基　　金：吉林省教育厅课题(JJKH20200783KJ)。

摘　　要：为了解决在低照度条件下,可见光成像设备采集的图像亮度低、细节不清晰等问题,提出一种基于亮度通道细节增强的低照度图像处理算法。首先,将图像从RGB转换到Lab颜色模型,将Lab模型中的亮度通道通过指数派生函数校正构造为光照分量,再经过Retinex增强得到初步增强图像。然后,采用结构张量和多尺度引导滤波分别对初步增强图像进行细节提取,并将两种方法提取的细节信息进行了融合。最后,将细节图像和初步增强图像融合得到了目标图像。实验结果主观上得到了亮度合适、细节清晰的增强图像,客观上在亮度失真、信息熵和能量梯度上均有良好且稳定的表现,表明该算法能够有效提高图像的亮度和细节信息,并保持自然的色彩和光照效果。To solve the problems of low brightness and unclear details of images collected by visible light imaging equipment under low-illumination conditions,a low-illumination image processing algorithm based on brightness channel detail enhancement is proposed.First,the image is converted from RGB to the Lab color model,the brightness channel in the Lab model is corrected to an illumination component by an exponential derivative function,and then the Retinex enhancement is performed to obtain a preliminary enhanced image.Then,the structure tensor and multi-scale guided image filtering are used to extract the details of the preliminary enhanced image,and the details extracted by the two methods are fused.Finally,the detail image and the preliminary enhanced image are merged to get the target image.Experimental results subjectively obtain the enhanced image with appropriate brightness and clear details,objectively have good and stable performance in brightness distortion,information entropy,and energy gradient,which shows that the proposed algorithm can effectively improve the brightness and detail information of the image,and maintain the natural color and lighting effect.

关 键 词：图像处理 图像增强 光照估计 细节增强 多尺度引导滤波 结构张量 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]