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.