基于亮度通道细节增强的低照度图像处理

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...

Low-Illuminance Image Processing Based on Brightness Channel Detail Enhancement

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.